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Cyber crime investigation: landscape, challenges, and future research directions.

1. Introduction

2. digital forensics, 2.1. host forensics, 2.2. mobile forensics, 2.2.1. investigation phases, 2.2.2. data extraction, 2.3. network forensics, 2.4. cloud forensics, 2.4.1. forensics as a service, 2.4.2. methods and frameworks, 2.4.3. cloud forensics and mobile devices, 3. online investigations, 3.1. sources of information, 3.1.1. open web, 3.1.2. deep web, 3.1.3. dark web, 3.2. specialized sources of information, 3.2.1. social media, 3.2.2. cryptocurrency flow, 3.3. data mining, 3.3.1. natural language processing, 3.3.2. social network analysis, 3.3.3. information extraction, 3.3.4. computer vision, 4. new forensic technologies, 4.1. automation, 4.2. machine learning (ai), 4.2.1. machine learning as an investigative tool, 4.2.2. machine learning as a criminal tool, 5. open issues and research directions.

• Technical issues (e.g., effectively implementing open-source intelligence tools used in investigations).
• Legal issues (e.g., obtaining legal basis for collecting evidence that is admissible in courts).
• Ethical issues (e.g., criminal profiling).

5.1. Technical Issues

5.2. legal issues, 5.3. ethical issues, 5.4. research directions of open issues, 6. conclusions and further research, author contributions, institutional review board statement, informed consent statement, conflicts of interest.

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Share and Cite

Horan, C.; Saiedian, H. Cyber Crime Investigation: Landscape, Challenges, and Future Research Directions. J. Cybersecur. Priv. 2021 , 1 , 580-596. https://doi.org/10.3390/jcp1040029

Horan C, Saiedian H. Cyber Crime Investigation: Landscape, Challenges, and Future Research Directions. Journal of Cybersecurity and Privacy . 2021; 1(4):580-596. https://doi.org/10.3390/jcp1040029

Horan, Cecelia, and Hossein Saiedian. 2021. "Cyber Crime Investigation: Landscape, Challenges, and Future Research Directions" Journal of Cybersecurity and Privacy 1, no. 4: 580-596. https://doi.org/10.3390/jcp1040029

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Research trends in cybercrime victimization during 2010–2020: a bibliometric analysis

Huong thi ngoc ho.

1 School of Journalism and Communication, Huazhong University of Science and Technology, Wuhan, Hubei China

Hai Thanh Luong

2 School of Global, Urban and Social Studies, RMIT University, Melbourne, Australia

Associated Data

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Research on cybercrime victimization is relatively diversified; however, no bibliometric study has been found to introduce the panorama of this subject. The current study aims to address this research gap by performing a bibliometric analysis of 387 Social Science Citation Index articles relevant to cybercrime victimization from Web of Science database during the period of 2010–2020. The purpose of the article is to examine the research trend and distribution of publications by five main fields, including time, productive authors, prominent sources, active institutions, and leading countries/regions. Furthermore, this study aims to determine the global collaborations and current gaps in research of cybercrime victimization. Findings indicated the decidedly upward trend of publications in the given period. The USA and its authors and institutions were likely to connect widely and took a crucial position in research of cybercrime victimization. Cyberbullying was identified as the most concerned issue over the years and cyber interpersonal crimes had the large number of research comparing to cyber-dependent crimes. Future research is suggested to concern more about sample of the elder and collect data in different countries which are not only European countries or the USA. Cross-nation research in less popular continents in research map was recommended to be conducted more. This paper contributed an overview of scholarly status of cybercrime victimization through statistical evidence and visual findings; assisted researchers to optimize their own research direction; and supported authors and institutions to build strategies for research collaboration.

Introduction

To date, the debate of cybercrime definition has been controversial which is considered as one of the five areas of cyber criminology (Ngo and Jaishankar 2017 ; Drew 2020 ). 1 Several terms are used to illustrate ‘cybercrime’, such as ‘high-tech crime’ (Insa 2007 ), ‘computer crime’ (Choi 2008 ; Skinner and Fream 1997 ), ‘digital crime’ (Gogolin 2010 ), or ‘virtual crime’ (Brenner 2001 ). ‘Cybercrime’, however, has been the most popular in the public parlance (Wall 2004 ). A propensity considers crime directly against computer as cybercrime, while other tendency asserts that any crime committed via internet or related to a computer is cybercrime (Marsh and Melville 2008 ; Wall 2004 ). Hence, there is a distinction between ‘true cybercrime’ or ‘high-tech’ cybercrime and ‘low-tech’ cybercrime (Wagen and Pieters 2020 ). Council of Europe defines ‘any criminal offense committed against or with the help of a computer network’ as cybercrime (Abdullah and Jahan 2020 , p. 90). Despite different approaches, cybercrime generally includes not only new types of crimes which have just occurred after the invention of computer and internet (Holt and Bossler 2014 ; Drew 2020 ) but also traditional types of crimes which took the advantages of information communication technology (ICT) as vehicle for illegal behaviors (Luong 2021 ; Nguyen and Luong 2020 ; Luong et al. 2019 ). Two main cybercrime categories identified, respectively, are cyber-dependent crime (hacking, malware, denial of service attacks) and cyber-enable crime (phishing, identity theft, cyber romance scam, online shopping fraud). Nevertheless, there are several different classifications of cybercrime such as cybercrime against certain individuals, groups of individuals, computer networks, computer users, critical infrastructures, virtual entities (Wagen and Pieters 2020 ); cyber-trespass, cyber-deceptions, cyber-pornography, and cyber-violence (Wall 2001 ).

Due to the common prevalence of cybercrime, the increasing threats of cybercrime victimization are obviously serious. Cybercrime victimization has become a crucial research subfield in recent years (Wagen and Pieters 2020 ). It is difficult to differ “forms of online victimization” and “acts that actually constitute a crime”, then it is usual for researchers to focus less on perspective of criminal law and consider any negative experiences online as cybercrime (Näsi et al. 2015 , p. 2). It was likely to lead to practical gaps between theory and practice in terms of investigating the nexus of offender and victims on cyberspace. In the light of literature review, numerous specific aspects of cybercrime victimization were investigated by questionnaire surveys or interview survey such as the prevalence of cybercrime victimization (Näsi et al. 2015 ; Whitty and Buchanan 2012 ); causes and predictors of cybercrime victimization (Abdullah and Jahan 2020 ; Algarni et al. 2017 ; Ilievski 2016 ; Jahankhani 2013 ; Kirwan et al. 2018 ; Näsi et al. 2015 ; Reyns et al. 2019 ; Saad et al. 2018 ); and the relationship between social networking sites (SNS) and cybercrime victimization (Das and Sahoo 2011 ; Algarni et al. 2017 ; Benson et al. 2015 ; Seng et al. 2018 ). To some extent, therefore, the current study examines cybercrime victimization in the large scale, referring to any negative experiences on cyberspace or computer systems. Nevertheless, no bibliometric analysis was found to show the research trend and general landscape of this domain.

Bibliometric is a kind of statistical analysis which uses information in a database to provide the depth insight into the development of a specified area (Leung et al. 2017 ). The present study aims to address this research gap by providing a bibliometric review of the relevant SSCI articles in WoS database during the period of 2010–2020. The pattern of publications, the productivity of main elements (authors, journals, institutions, and countries/regions), statistic of citations, classification of key terms, research gaps, and other collaborations will be presented and discussed in section four and five after reviewing literatures and presenting our methods conducted. This article contributes an overview of research achievements pertaining to cybercrime victimization in the given period through statistical evidence and visual findings; assists researchers to perceive clearly about the key positions in research maps of this field, and obtain more suggestions to develop their own research direction.

Literature review

Cybercrime victimization.

Cybercrime victimization may exist in two levels including institutional and individual level (Näsi et al. 2015 ). For the former, victim is governments, institutions, or corporations, whereas for the latter, victim is a specific individual (Näsi et al. 2015 ). A wide range of previous studies concerned about individual level of victim and applied Lifestyle Exposure Theory (LET), Routine Activity Theory (RAT) and General Theory of Crime to explain cybercrime victimization (Choi 2008 ; Holt and Bossler 2009 ; Ngo and Paternoster 2011 ). Basing on these theories, situational and individual factors were supposed to play an important role in understanding cybercrime victimization (Choi 2008 ; Van Wilsem 2013 ). However, there was another argument that situational and individual factors did not predict cybercrime victimization (Ngo and Paternoster 2011 ; Wagen and Pieters 2020 ). Overall, most of those studies just focused only one distinctive kind of cybercrime such as computer viruses, malware infection, phishing, cyberbullying, online harassment, online defamation, identity theft, cyberstalking, online sexual solicitation, cyber romance scams or online consumer fraud. Referring to results of the prior research, some supported for the applicability of mentioned theories but other did not share the same viewpoint (Leukfeldt and Yar 2016 ). It was hard to evaluate the effect of LET or RAT for explanation of cybercrime victimization because the nature of examined cybercrime were different (Leukfeldt and Holt 2020 ; Leukfeldt and Yar 2016 ).

Previous research determined that cybercrime victimization was more common in younger group compared to older group because the young is the most active online user (Näsi et al. 2015 ; Oksanen and Keipi 2013 ) and males tended to become victims of cybercrime more than females in general (Näsi et al. 2015 ). However, findings might be different in research which concerned specific types of cybercrime. Women were more likely to be victims of the online romance scam (Whitty and Buchanan 2012 ) and sexual harassment (Näsi et al. 2015 ), while men recorded higher rate of victimization of cyber-violence and defamation. Other demographic factors were also examined such as living areas (Näsi et al. 2015 ), education (Oksanen and Keipi 2013 ; Saad et al. 2018 ) and economic status (Oksanen and Keipi 2013 ; Saad et al. 2018 ). Furthermore, several prior studies focus on the association of psychological factors and cybercrime victimization, including awareness and perception (Ariola et al. 2018 ; Saridakis et al. 2016 ), personality (Kirwan et al. 2018 ; Orchard et al. 2014 ; Parrish et al. 2009 ), self-control (Ilievski 2016 ; Ngo and Paternoster 2011 ; Reyns et al. 2019 ), fear of cybercrime (Lee et al. 2019 ), online behaviors (Al-Nemrat and Benzaïd 2015 ; Saridakis et al. 2016 ). Psychological factors were assumed to have effects on cybercrime victimization at distinctive levels.

Another perspective which was much concerned by researchers was the relationship between cybercrime victimization and SNS. SNS has been a fertile land for cybercriminals due to the plenty of personal information shared, lack of guard, the availability of communication channels (Seng et al. 2018 ), and the networked nature of social media (Vishwanath 2015 ). When users disclosed their personal information, they turned themselves into prey for predators in cyberspace. Seng et al. ( 2018 ) did research to understand impact factors on user’s decision to react and click on suspicious posts or links on Facebook. The findings indicated that participants’ interactions with shared contents on SNS were affected by their relationship with author of those contents; they often ignored the location of shared posts; several warning signals of suspicious posts were not concerned. Additionally, Vishwanath ( 2015 ) indicated factors that led users to fall victims on the SNS; Algarni et al. ( 2017 ) investigated users’ susceptibility to social engineering victimization on Facebook; and Kirwan et al. ( 2018 ) determined risk factors resulting in falling victims of SNS scam.

Bibliometric of cybercrime victimization

“Bibliometric” is a term which was coined by Pritchard in 1969 and a useful method which structures, quantifies bibliometric information to indicate the factors constituting the scientific research within a specific field (Serafin et al. 2019 ). Bibliometric method relies on some basic types of analysis, namely co-authorship, co-occurrence, citation, co-citation, and bibliographic coupling. This method was employed to various research domains such as criminology (Alalehto and Persson 2013 ), criminal law (Jamshed et al. 2020 ), marketing communication (Kim et al. 2019 ), social media (Chen et al. 2019 ; Gan and Wang 2014 ; Leung et al. 2017 ; Li et al. 2017 ; You et al. 2014 ; Zyoud et al. 2018 ), communication (Feeley 2008 ), advertising (Pasadeos 1985 ), education (Martí-Parreño et al. 2016 ).

Also, there are more and more scholars preferring to use bibliometric analysis on cyberspace-related subject such as: cyber behaviors (Serafin et al. 2019 ), cybersecurity (Cojocaru and Cojocaru 2019 ), cyber parental control (Altarturi et al. 2020 ). Serafin et al. ( 2019 ) accessed the Scopus database to perform a bibliometric analysis of cyber behavior. All documents were published by four journals: Cyberpsychology, Behavior and Social Networking (ISSN: 21522723), Cyberpsychology and Behavior (ISSN: 10949313) , Computers in Human Behavior (ISSN: 07475632) and Human–Computer Interaction (ISSN: 07370024), in duration of 2000–2018. Findings indicated the use of Facebook and other social media was the most common in research during this period, while psychological matters were less concerned (Serafin et al. 2019 ). Cojocaru and Cojocaru ( 2019 ) examined the research status of cybersecurity in the Republic of Moldavo, then made a comparison with the Eastern Europe countries’ status. This study employed bibliometric analysis of publications from three data sources: National Bibliometric Instrument (database from Republic of Moldavo), Scopus Elsevier and WoS. The Republic of Moldavo had the moderate number of scientific publications on cybersecurity; Russian Federation, Poland, Romania, Czech Republic, and Ukraine were the leading countries in Eastern Europe area (Cojocaru and Cojocaru 2019 ). Altarturi et al. ( 2020 ) was interested in bibliometric analysis of cyber parental control, basing on publications between 2000 and 2019 in Scopus and WoS. This research identified some most used keywords including ‘cyberbullying’, ‘bullying’, ‘adolescents’ and ‘adolescence’, showing their crucial position in the domain of cyber parental control (Altarturi et al. 2020 ). ‘Cyber victimization’ and ‘victimization’ were also mentioned as the common keywords by Altarturi et al. ( 2020 ). Prior research much focus on how to protect children from cyberbullying. Besides, four online threats for children were determined: content, contact, conduct and commercial threats (Altarturi et al. 2020 ).

Generally, it has been recorded several published bibliometric analyses of cyber-related issues but remained a lack of bibliometric research targeting cybercrime victimization. Thus, the present study attempts to fill this gap, reviewing the achievements of existed publications as well as updating the research trend in this field.

In detail, our current study aims to address four research questions (RQs):

What is overall distribution of publication based on year, institutions and countries, sources, and authors in cybercrime victimization?

Which are the topmost cited publications in terms of cybercrime victimization?

Who are the top co-authorships among authors, institutions, and countries in research cybercrime victimization?

What are top keywords, co-occurrences and research gaps in the field of cybercrime victimization?

Data collection procedure

Currently, among specific approaches in cybercrime’s fileds, WoS is “one of the largest and comprehensive bibliographic data covering multidisciplinary areas” (Zyoud et al. 2018 , p. 2). This paper retrieved data from the SSCI by searching publications of cybercrime victimization on WoS database to examine the growth of publication; top keywords; popular topics; research gaps; and top influential authors, institutions, countries, and journals in the academic community.

This paper employed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for data collection procedure. For timeline, we preferred to search between 2010 and 2020 on the WoS system with two main reasons. First, when the official update of the 2009 PRISMA Statement had ready upgraded with the specific guidelines and stable techniques, we consider beginning since 2010 that is timely to test. Secondly, although there are several publications from the early of 2021 to collect by the WoS, its updated articles will be continued until the end of the year. Therefore, we only searched until the end of 2020 to ensure the full updates.

To identify publications on cybercrime victimization, the study accessed WoS and used two keywords for searching: ‘cybercrime victimization’ or ‘cyber victimization’ after testing and looking for some terminology-related topics. Accordingly, the paper applied a combination of many other searching terms besides two selected words such as “online victimization”, “victim of cybercrime”, “phishing victimization”, “online romance victimization”, “cyberstalking victim”, “interpersonal cybercrime victimization”, or “sexting victimization”, the results, however, were not really appropriate. A lot of papers did not contain search keywords in their titles, abstracts, keywords and were not relavant to study topic. After searching with many different terms and comparing the results, the current study selected the two search terms for the most appropriate articles. The query result consisted of 962 documents. Basing on the result from preliminary searching, retrieved publications were refined automatically on WoS by criteria of timespan, document types, language, research areas, and WoS Index as presented in Table ​ Table1. 1 . Accordingly, the criteria for automatic filter process were basic information of an articles and classified clearly in WoS system so the results reached high accuracy. The refined results are 473 articles.

Criteria for automatic filter

After automatic filters, file of data was converted to Microsoft Excel 2016 for screening. The present study examined titles and abstracts of 473 articles to assess the eligibility of each publication according to the relevance with given topic. There are 387 articles are eligible,while 86 irrelevant publications were excluded.

Data analysis

Prior to data analysis, the raw data were cleaned in Microsoft Excel 2016. Different forms of the same author’s name were corrected for consistency, for example “Zhou, Zong-Kui” and “Zhou Zongkui”, “Van Cleemput, Katrien” and “Van Cleemput, K.”, “Williams, Matthew L.” and “Williams, Matthew”. Similarly, different keywords (single/plural or synonyms) used for the same concept were identified and standardized such as “victimization” and “victimisation”; “adolescent” and “adolescents”; “cyber bullying”, “cyber-bullying” and “cyberbullying”; “routine activity theory” and “routine activities theory”.

The data were processed by Microsoft Excel 2016 and VOS Viewer version 1.6.16; then it was analyzed according to three main aspects. First, descriptive statistic provided evidence for yearly distribution and growth trend of publications, frequency counts of citations, the influential authors, the predominant journals, the top institutions and countries/territories, most-cited publications. Second, co-authorship and co-occurrence analysis were constructed and visualized by VOS Viewer version 1.6.16 to explore the network collaborations. Finally, the current study also investigated research topics through content analysis of keywords. The authors’ keywords were classified into 15 themes, including: #1 cybercrime; #2 sample and demographic factors; #3 location; #4 theory; #5 methodology; #6 technology, platforms and related others; #7 psychology and mental health; #8 physical health; #9 family; #10 school; #11 society; #12 crimes and deviant behaviors; #13 victim; #14 prevention and intervention; and #15 others. Besides, the study also added other keywords from titles and abstracts basing on these themes, then indicated aspects examined in previous research.

In this section, all findings corresponding with four research questions identified at the ouset of this study would be illustrated (Fig.  1 ).

PRISMA diagram depicts data collection from WoS database

Distribution of publication

Distribution by year, institutions and countries.

Basing on retrieved data, it was witnessed an increasing trend of articles relevant to cybercrime victimization in SSCI list during the time of 2010–2020 but it had slight fluctuations in each year as shown in Fig.  2 . The total number of articles over this time was 387 items, which were broken into two sub-periods: 2010–2014 and 2015–2020. It is evident that the latter period demonstrated the superiority of the rate of articles (79.33%) compared to the previous period (20.67%). The yearly quantity of publications in this research subject was fewer than forty before 2015. Research of cybercrime victimization reached a noticeable development in 2016 with over fifty publications, remained the large number of publications in the following years and peaked at 60 items in 2018.

Annual distribution of publications

Distribution by institutions and countries

Table ​ Table2 2 shows the top contributing institutions according to the quantity of publications related to cybercrime victimization. Of the top institutions, four universities were from the USA, two ones were from Spain, two institutions were from Australia and the rest ones were from Czech Republic, Belgium, Greece, and Austria. Specifically, Masaryk University (17 documents) became the most productive publishing institution, closely followed by Michigan State University (16 documents). The third and fourth places were University of Antwerp (13 documents) and Weber State University (10 documents). Accordingly, the institutions from The USA and Europe occupied the vast majority.

Top contributing institutions based on total publications

TP total publications, TC total citations for the publications reviewed, AC average citations per document

In Table ​ Table2, 2 , University of Seville (total citations: 495, average citations: 70.71) ranked first and University of Cordoba (total citations: 484, average citations: 60.50) stayed at the second place in both total citations and average citations.

Referring to distribution of publications by countries, there were 45 countries in database contributing to the literature of cybercrime victimization. The USA recorded the highest quantity of papers, creating an overwhelming difference from other countries (159 documents) as illustrated in Fig.  3 . Of the top productive countries, eight European countries which achieved total of 173 publications were England (39 documents), Spain (34 documents), Germany (22 documents), Netherlands (18 documents), Italy (17 documents) and Czech Republic (17 documents), Belgium (14 documents), Greece (12 documents). Australia ranked the fourth point (32 documents), followed by Canada (30 documents). One Asian country which came out seventh place, at the same position with Netherlands was China (18 documents).

Top productive countries based on the number of publications

Distribution by sources

Table ​ Table3 3 enumerates the top leading journals in the number of publications relevant to cybercrime victimization. The total publications of the first ranking journal— Computers in Human Behavior were 56, over twice as higher as the second raking journal— Cyberpsychology, Behavior and Social Networking (24 articles). Most of these journals have had long publishing history, starting their publications before 2000. Only three journals launched after 2000, consisting of Journal of School Violence (2002), Cyberpsychology: Journal of Psychosocial Research on Cyberspace (2007) and Frontiers in Psychology (2010). Besides, it is remarked that one third of the top journals focuses on youth related issues: Journal of Youth and Adolescence , Journal of Adolescence, School Psychology International and Journal of School Violence .

Top leading journals based on the quantity of publications

SPY Started Publication Year

In Table ​ Table3, 3 , relating to total citations, Computers in Human Behavior remained the first position with 2055 citations. Journal of Youth and Adolescence had total 1285 citations, ranked second and followed by Aggressive Behavior with 661 citations. In terms of average citations per documents, an article of Journal of Youth and Adolescence was cited 67.63 times in average, much higher than average citations of one in Computers in Human Behavior (36.70 times). The other journals which achieved the high number of average citations per document were School Psychology International (59.00 times), Journal of Adolescence (44.83 times) and Aggressive Behavior (44.07 times).

Distribution by authors

Table ​ Table4 4 displays ten productive authors based on article count; total citations of each author and their average citations per document are also included. Michelle F. Wright from Pennsylvania State University ranked first with twenty publications, twice as higher as the second positions, Thomas J. Holt (10 articles) from Michigan State University and Bradford W. Reyns (10 articles) from Weber State University. Rosario Ortega-Ruiz from University of Cordoba stayed at the third place in terms of total publications but the first place in aspect of total citations (483 citations) and the average citations (60.38 times).

Top productive authors based on article count

Of the most productive authors based on total publications, there were three authors from universities in the USA; one from the university in Canada (Brett Holfeld); the others were from institutions in Euro, including Spain (Rosario Ortega-Ruiz), Greece (Constantinos M. Kokkinos) and Belgium (Heidi Vandebosch), Netherlands (Rutger Leukfeldt) and Austria (Takuya Yanagida and Christiane Spiel).

Most-cited publications

The most-cited literature items are displayed in Table ​ Table5. 5 . The article which recorded the highest number of citations was ‘Psychological, Physical, and Academic Correlates of Cyberbullying and Traditional Bullying’ (442 citations) by Robin M. Kowalski et al. published in Journal of Adolescent Health , 2013. Seven of ten most-cited articles were about cyberbullying; focused on youth population; made comparisons between cyberbullying and traditional bullying; analyzed the impact of several factors such as psychological, physical, academic factors or use of Internet; discussed on preventing strategies. The other publications studied victimization of cyberstalking and cyber dating abuse. All most-cited articles were from 2015 and earlier.

The most-cited publications in subject of cybercrime victimization during 2010–2020

Of the top productive authors, only Bradford W. Reyns had an article appeared in the group of most-cited publications. His article ‘Being Pursued Online: Applying Cyberlifestyle-Routine Activities Theory to Cyberstalking Victimization’ (2011) was cited 172 times.

Co-authorship analysis

“Scientific collaboration is a complex social phenomenon in research” (Glänzel and Schubert 2006 , p. 257) and becomes the increasing trend in individual, institutional and national levels. In bibliometric analysis, it is common to assess the productivity and international collaboration of research; identify key leading researchers, institutions, or countries (E Fonseca et al. 2016 ) as well as potential collaborators in a specific scientific area (Romero and Portillo-Salido 2019 ) by co-authorship analysis which constructs networks of authors and countries (Eck and Waltman 2020 ).

This section analyses international collaboration relevant to research of cybercrime victimization among authors, institutions, and countries during 2010–2020 through visualization of VOS Viewer software.

Collaboration between authors

Referring to the threshold of choose in this analysis, minimum number of documents of author is three and there were 80 authors for final results. Figure  4 illustrates the relationships between 80 scientists who study in subject of cybercrime victimization during 2010–2020. It shows several big groups of researchers (Wright’s group, Vandebosch’s group, or Holt’s group), while numerous authors had limited or no connections to others (Sheri Bauman, Michelle K. Demaray or Jennifer D. Shapka).

Collaboration among authors via network visualization (threshold three articles for an author, displayed 80 authors)

Figure  5 displayed a significant network containing 23 authors who were active in collaboration in detail. The displayed items in Fig.  5 are divided into five clusters coded with distinctive colors, including red, green, blue, yellow, and purple. Each author item was represented by their label and a circle; the size of label and circle are depended on the weight of the item, measured by the total publications (Eck and Waltman 2020 ). The thickness of lines depends on the strength of collaboration (Eck and Waltman 2020 ).

Collaboration among authors via network visualization (threshold three articles for an author, displayed 23 authors)

The most significant cluster was red one which is comprised of six researchers: Michelle F. Wright, Sebastian Wachs, Yan Li, Anke Gorzig, Manuel Gamez-Guadix and Esther Calvete. The remarked author for the red cluster was Michelle F. Wright whose value of total link strength is 24. She had the strongest links with Sebastian Wachs; closely link with Yan Li, Anke Gorzig, Manuel Gamez-Guadix and collaborated with authors of yellow cluster, including Shanmukh V. Kamble, Li Lei, Hana Machackova, Shruti Soudi as well as Takuya Yanagida of blue cluster. Michelle F. Wright who obtained the largest number of published articles based on criteria of this study made various connections with other scholars who were from many different institutions in the world. This is also an effective way to achieve more publications.

Takuya Yanagida was the biggest node for the blue cluster including Petra Gradinger, Daniel Graf, Christiane Spiel, Dagmar Strohmeier. Total link strength for Takuya Yanagida was 28; twelve connections. It is observed that Takuya Yanagida’ s research collaboration is definitely active. Besides, other research groups showed limited collaborations comparing with the red and blue ones.

Collaboration between institutions

The connections among 156 institutions which published at least two documents per one are shown in Fig.  6 . Interestingly, there is obvious connections among several distinctive clusters which were coded in color of light steel blue, orange, purple, steel blue, green, red, yellow, light red, dark turquoise, light blue, brown and light green. These clusters created a big chain of connected institutions and were in the center of the figure, while other smaller clusters or unlinked bubbles (gray color) were distributed in two sides. The biggest chain consisted of most of productive institutions such as Masaryk University, Michigan State University, University of Antwerp, Weber State University, University of Cordoba, Edith Cowan University, University of Cincinnati, University of Victoria, University of Vienna, and University of Seville.

Collaboration among institutions via network visualization (threshold two articles for an institution, 156 institutions were displayed)

Light steel blue and orange clusters presented connections among organizations from Australia. Light green included institutions from Netherland, while turquoise and light blue consisted of institutions from the USA. Yellow cluster was remarked by the various collaborations among institutions from China and Hong Kong Special Administrative Region (Renmin University of China and South China Normal University, University of Hong Kong, the Hong Kong Polytechnic University and the Chinese University of Hong Kong), the USA (University of Virginia), Cyprus (Eastern Mediterranean University), Japan (Shizuoka University), India (Karnataka University) and Austria (University Applied Sciences Upper Austria). Central China Normal University is another Chinese institution which appeared in Fig.  5 , linking with Ministry of Education of the People’s Republic of China, Suny Stony Brook and University of Memphis from the USA.

Masaryk University and Michigan State University demonstrated their productivity in both the quantity of publications and the collaboration network. They were active in research collaboration, reaching twelve and eleven links, respectively, with different institutions, but focused much on networking with institutions in the USA and Europe.

Collaboration between countries

The collaboration among 45 countries which published at least one SSCI documents of cybercrime victimization during the given period was examined in VOS Viewer but just 42 items were displayed via overlay visualization. Figure  7 depicts the international collaborations among significant countries. The USA is the biggest bubble due to its biggest number of documents and shows connections with 26 countries/regions in Euro, Asia, Australia, Middle East. Excepting European countries, England collaborate with the USA, Australia, South Korea, Japan, Thailand, Singapore, Sri Lanka, and Colombia. Spain and Germany almost focus on research network within Euro. China has the strongest tie with the USA, link with Australia, Germany, Czech Republic, Austria, Cyprus and Turkey, Japan, Indian, Vietnam.

Collaboration among countries via overlay visualization

Color bar in Fig.  7 is determined by the average publication year of each country and the color of circles based on it. It is unsurprised that the USA, Australia, England, or Spain shows much research experience in this field and maintain the large number of publications steadily. Interestingly, although the average publication year of South Korea or Cyprus was earlier than other countries (purple color), their quantities of documents were moderate. The new nodes (yellow circles) in the map included Vietnam, Norway, Pakistan, Ireland, Scotland, Switzerland.

Keywords and co-occurrence

The present paper examined the related themes and contents in research of cybercrime victimization during 2010–2020 through collecting author keywords, adding several keywords from tiles and abstracts. Besides, this study also conducted co-occurrence analysis of author keywords to show the relationships among these keywords.

The keywords were collected and categorized into 15 themes in Table ​ Table6, 6 , including cybercrime; sample and demographic factors; location; theory; methodology; technology, platform, and related others; psychology and mental health; physical health; family; school; society; crimes and other deviant behaviors; victim; prevention and intervention; and others.

Statistic of keywords in themes

These keywords were most of author keyword, adding a few selected keywords from the titles and abstracts by the author of this current study

In the theme of cybercrime, there were numerous types of cybercrimes such as cyberbullying, cyber aggression, cyberstalking, cyber harassment, sextortion and other cyber dating crimes, cyber fraud, identity theft, phishing, hacking, malware, or ransomware. Generally, the frequency of interpersonal cybercrimes or cyber-enable crimes was much higher than cyber-dependent crimes. Cyberbullying was the most common cybercrime in research.

Relating to sample and demographic factors, there were sample of children, adolescent, adults, and the elder who were divided into more detail levels in each research; however, adolescent was the most significant sample. Besides, demographic factor of gender received a remarked concern from scholars.

It is usual that most of the research were carried out in one country, in popular it was the USA, Spain, Germany, England, Australia, Canada or Netherland but sometimes the new ones were published such as Chile, Vietnam, Thailand or Singapore. It was witnessed that some studies showed data collected from a group of countries such as two countries (Canada and the United State), three countries (Israel, Litva, Luxembourg), four countries (the USA, the UK, Germany, and Finland), or six Europe countries (Spain, Germany, Italy, Poland, the United Kingdom and Greece).

A wide range of theories were applied in this research focusing on criminological and psychological theories such as Routine Activities Theory, Lifestyle—Routine Activities Theory, General Strain Theory, the Theory of Reasoned Action or Self-control Theory.

Table ​ Table6 6 indicated a lot of different research methods covering various perspective of cybercrime victimization: systematic review, questionnaire survey, interview, experiment, mix method, longitudinal study, or cross-national research; many kinds of analysis such as meta-analysis, social network analysis, latent class analysis, confirmatory factor analysis; and a wide range of measurement scales which were appropriate for each variable.

Topic of cybercrime victimization had connections with some main aspects of technology (information and communication technologies, internet, social media or technology related activities), psychology (self-esteem, fear, attitude, personality, psychological problems, empathy, perceptions or emotion), physical health, family (parents), school (peers, school climate), society (norms, culture, social bonds), victim, other crimes (violence, substance use), prevention and intervention.

Co-occurrence analysis was performed with keywords suggested by authors and the minimum number of occurrences per word is seven. The result showed 36 frequent keywords which clustered into five clusters as illustrated in Fig.  8 .

Co-occurrence between author keywords via network visualization (the minimum number of occurrences per word is seven, 36 keywords were displayed)

Figure  8 illustrates some main issues which were concerned in subject of cybercrime victimization, as well as the relationship among them. Fifteen most frequent keywords were presented by big bubbles, including: ‘cyberbullying’ (174 times), ‘cyber victimization’ (90 times), ‘adolescent’ (79 times), ‘bullying’ (66 times), ‘victimization’ (56 times), ‘cybercrime’ (40 times), ‘cyber aggression’ (37 times), ‘depression’ (23 times), ‘aggression’ (14 times), ‘routine activities theory’ (13 times), ‘cyberstalking’ (11 times), ‘gender’ (11 times), ‘longitudinal’ (10 times), ‘peer victimization’ (10 times) and ‘self-esteem’ (10 times).

‘Cyberbullying’ linked with many other keywords, demonstrating the various perspectives in research of this topic. The thick lines which linked ‘cyberbullying’ and ‘bullying’, ‘adolescent’, ‘cyber victimization’, ‘victimization’ showed the strong connections between them; there were close relationship between ‘cyber aggression’, ‘bystander”, ‘self-esteem’ or ‘moral disengagement’ and ‘cyberbullying’.

‘Cybercrime’ had strong links with ‘victimization’, ‘routine activities theory’. In Fig.  8 , the types of cybercrime which occurred at least seven times were: cyberbullying, cyber aggression, hacking, cyberstalking, and cyber dating abuse.

The increasing trend over the years reveals the increasing concern of scholarly community on this field, especially in the boom of information technology and other communication devices and the upward trend in research of cyberspace-related issues (Altarturi et al. 2020 ; Leung et al. 2017 ; Serafin et al. 2019 ). It predicts the growth of cybercrime victimization research in future.

Psychology was the more popular research areas in database, defeating criminology penology. As part of the ‘human factors of cybercrime’, human decision-making based on their psychological perspectives plays as a hot topic in cyber criminology (Leukfeldt and Holt 2020 ). Then, it is observed that journals in psychology field was more prevalent in top of productive sources. Besides, journal Computers in Human Behavior ranked first in total publications, but Journal of Youth and Adolescence ranked higher place in the average citations per document. Generally, top ten journals having highest number of publications on cybercrime victimization are highly qualified ones and at least 10 years in publishing industry.

The USA demonstrated its leading position in the studied domain in terms of total publications as well as the various collaborations with other countries. The publications of the USA occupied much higher than the second and third countries: England and Spain. It is not difficult to explain for this fact due to the impressive productivity of institutions and authors from the USA. A third of top twelve productive institutions were from the USA. Three leading positions of top ten productive authors based on document count were from institutions of the USA, number one was Michelle F. Wright; others were Thomas J. Holt and Bradford W. Reyns.

Furthermore, these authors also participated in significant research groups and become the important nodes in those clusters. The most noticeable authors in co-authors network were Michelle F. Wright. The US institutions also had strong links in research network. The USA was likely to be open in collaboration with numerous countries from different continents in the world. It was assessed to be a crucial partner for others in the international co-publication network (Glänzel and Schubert 2006 ).

As opposed to the USA, most of European countries prefer developing research network within Europe and had a limited collaboration with other areas. Australia, the USA, or Japan was in a small group of countries which had connections with European ones. Nevertheless, European countries still showed great contributions for research of cybercrime victimization and remained stable links in international collaboration. The prominent authors from Euro are Rosario Ortega-Ruiz, Constantinos M. Kokkinos or Rutger Leukfeldt.

It is obvious that the limited number of publications from Asia, Middle East, Africa, or other areas resulted in the uncomprehensive picture of studied subject. For example, in the Southeast Asia, Malaysia and Vietnam lacked the leading authors with their empirical studies to review and examine the nature of cybercrimes, though they are facing to practical challenges and potential threats in the cyberspace (Lusthaus 2020a , b ). The present study indicated that Vietnam, Ireland, or Norway was the new nodes and links in research network.

Several nations which had a small number of publications such as Vietnam, Thailand, Sri Lanka, or Chile started their journey of international publications. It is undeniable that globalization and the context of global village (McLuhan 1992 ) requires more understanding about the whole nations and areas. Conversely, each country or area also desires to engage in international publications. Therefore, new nodes and clusters are expected to increase and expand.

The findings indicated that cyberbullying was the most popular topic on research of cybercrime victimization over the given period. Over a half of most-cited publications was focus on cyberbullying. Additionally, ‘cyberbullying’ was the most frequent author keyword which co-occurred widely with distinctive keywords such as ‘victimization’, ‘adolescents’, ‘bullying’, ‘social media’, ‘internet’, ‘peer victimization’ or ‘anxiety’.

By reviewing keywords, several research gaps were indicated. Research samples were lack of population of the children and elders, while adolescent and youth were frequent samples of numerous studies. Although young people are most active in cyberspace, it is still necessary to understand other populations. Meanwhile, the elderly was assumed to use information and communication technologies to improve their quality of life (Tsai et al. 2015 ), their vulnerability to the risk of cybercrime victimization did not reduce. Those older women were most vulnerable to phishing attacks (Lin et al. 2019 ; Oliveira et al. 2017 ). Similarly, the population of children with distinctive attributes has become a suitable target for cybercriminals, particularly given the context of increasing online learning due to Covid-19 pandemic impacts. These practical gaps should be prioritized to focus on research for looking the suitable solutions in the future. Besides, a vast majority of research were conducted in the scope of one country; some studies collected cross-national data, but the number of these studies were moderate and focused much on developed countries. There are rooms for studies to cover several countries in Southeast Asia or South Africa.

Furthermore, although victims may be both individuals and organizations, most of research concentrated much more on individuals rather than organizations or companies. Wagen and Pieters ( 2020 ) indicated that victims include both human and non-human. They conducted research covering cases of ransomware victimization, Bonet victimization and high-tech virtual theft victimization and applying Actor-Network Theory to provide new aspect which did not aim to individual victims. The number of this kind of research, however, was very limited. Additionally, excepting cyberbullying and cyber aggression were occupied the outstanding quantity of research, other types of cybercrime, especially, e-whoring, or social media-related cybercrime should still be studied more in the future.

Another interesting topic is the impact of family on cybercrime victimization. By reviewing keyword, it is clear that the previous studies aimed to sample of adolescent, hence, there are many keywords linking with parents such as ‘parent-adolescent communication’, ‘parent-adolescent information sharing’, ‘parental mediation’, ‘parental monitoring of cyber behavior’, ‘parental style’. As mentioned above, it is necessary to research more on sample of the elder, then, it is also essential to find out how family members affect the elder’s cybercrime victimization.

It is a big challenge to deal with problems of cybercrime victimization because cybercrime forms become different daily (Näsi et al. 2015 ). Numerous researchers engage in understanding this phenomenon from various angles. The current bibliometric study assessed the scholarly status on cybercrime victimization during 2010–2020 by retrieving SSCI articles from WoS database. There is no study that applied bibliometric method to research on the examined subject. Hence, this paper firstly contributed statistical evidence and visualized findings to literature of cybercrime victimization.

Statistical description was applied to measure the productive authors, institutions, countries/regions, sources, and most-cited documents, mainly based on publication and citation count. The international collaborations among authors, institutions, and countries were assessed by co-authors, while the network of author keywords was created by co-occurrence analysis. The overall scholarly status of cybercrime victimization research was drawn clearly and objectively. The research trend, popular issues and current gaps were reviewed, providing numerous suggestions for policymakers, scholars, and practitioners about cyber-related victimization (Pickering and Byrne 2014 ). Accordingly, the paper indicated the most prevalent authors, most-cited papers but also made summary of contributions of previous research as well as identified research gaps. First, this article supports for PhD candidates or early-career researchers concerning about cybercrime victimization. Identifying the leading authors, remarked journals, or influencing articles, gaps related to a specific research topic is important and useful task for new researchers to start their academic journey. Although this information is relatively simple, it takes time and is not easy for newcomers to find out, especially for ones in poor or developing areas which have limited conditions and opportunities to access international academic sources. Thus, the findings in the current paper provided for them basic but necessary answers to conduct the first step in research. Secondly, by indicating research gaps in relevance to sample, narrow topics or scope of country, the paper suggests future study fulfilling them to complete the field of cybercrime victimization, especial calling for publications from countries which has had a modest position in global research map. Science requires the balance and diversity, not just focusing on a few developed countries or areas. Finally, the present study assists researchers and institutions to determined strategy and potential partners for their development of research collaborations. It not only improve productivity of publication but also create an open and dynamic environment for the development of academic field.

Despite mentioned contributions, this study still has unavoidable limitations. The present paper just focused on SSCI articles from WoS database during 2010–2020. It did not cover other sources of databases that are known such as Scopus, ScienceDirect, or Springer; other types of documents; the whole time; or articles in other languages excepting English. Hence it may not cover all data of examined subject in fact. Moreover, this bibliometric study just performed co-authorship and co-occurrence analysis. The rest of analysis such as citation, co-citation and bibliographic coupling have not been conducted. Research in the future is recommended to perform these kinds of assessment to fill this gap. To visualize the collaboration among authors, institutions, countries, or network of keywords, this study used VOS Viewer software and saved the screenshots as illustrations. Therefore, not all items were displayed in the screenshot figures.

Data availability

Declarations.

The authors declare that they have no competing interest.

1 In the ‘commemorating a decade in existence of the International Journal of Cyber Criminoogy’, Ngo and Jaishankar ( 2017 ) called for further research with focusing on five main areas in the Cyber Criminiology, including (1) defining and classifying cybercrime, (2) assessing the prevalence, nature, and trends of cybercrime, (3) advancing the field of cyber criminology, (4) documenting best practices in combating and preventing cybercrime, and (5) cybercrime and privacy issues.

Contributor Information

Huong Thi Ngoc Ho, Email: moc.liamg@252nhgnouH .

Hai Thanh Luong, Email: [email protected] .

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• Published: 23 February 2023

Exploring the global geography of cybercrime and its driving forces

• Shuai Chen   ORCID: orcid.org/0000-0003-3623-1532 1 , 2 ,
• Mengmeng Hao   ORCID: orcid.org/0000-0001-5086-6441 1 , 2 ,
• Fangyu Ding   ORCID: orcid.org/0000-0003-1821-531X 1 , 2 ,
• Dong Jiang 1 , 2 ,
• Jiping Dong 1 , 2 ,
• Shize Zhang 3 ,
• Qiquan Guo 1 &
• Chundong Gao 4  

Humanities and Social Sciences Communications volume  10 , Article number:  71 ( 2023 ) Cite this article

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• Criminology
• Science, technology and society

Cybercrime is wreaking havoc on the global economy, national security, social stability, and individual interests. The current efforts to mitigate cybercrime threats are primarily focused on technical measures. This study considers cybercrime as a social phenomenon and constructs a theoretical framework that integrates the social, economic, political, technological, and cybersecurity factors that influence cybercrime. The FireHOL IP blocklist, a novel cybersecurity data set, is used to map worldwide subnational cybercrimes. Generalised linear models (GLMs) are used to identify the primary factors influencing cybercrime, whereas structural equation modelling (SEM) is used to estimate the direct and indirect effects of various factors on cybercrime. The GLM results suggest that the inclusion of a broad set of socioeconomic factors can significantly improve the model’s explanatory power, and cybercrime is closely associated with socioeconomic development, while their effects on cybercrime differ by income level. Additionally, results from SEM further reveals the causal relationships between cybercrime and numerous contextual factors, demonstrating that technological factors serve as a mediator between socioeconomic conditions and cybercrime.

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Introduction.

Cybercrime is a broad term used by government, businesses, and the general public to account for a variety of criminal activities and harmful behaviours involving the adoption of computers, the internet, or other forms of information communications technologies (ICTs) (Wall, 2007 ). As an emerging social phenomenon in the information age, cybercrime has aroused growing concern around the world due to its high destructiveness and widespread influence. In 2017, the WannaCry ransomware attack affected more than 230,000 computers across 150 countries, resulting in economic losses of more than 4 billion dollars and posing a serious danger to the global education, government, finance, and healthcare sectors (Ghafur et al., 2019 ; Castillo and Falzon, 2018 ; Mohurle and Patil, 2017 ). Although there is currently no precise and universally accepted definition of cybercrime (Phillips et al., 2022 ; Holt and Bossler, 2014 ), it is generally acknowledged that the term covers both traditional crimes that are facilitated or amplified by utilising ICTs as well as new types of crimes that emerged with the advent of ICTs (Ho and Luong, 2022 ). Based on the role of technology in the commission of the crime, the most widely utilised typology divides cybercrime into cyber-dependent crime (such as hacking, distributed denial of service, and malware) and cyber-enabled crime (online fraud, digital piracy, cyberbullying) (Brenner, 2013 ; Sarre et al., 2018 ; McGuire and Dowling, 2013 ). Along with the rapid development of ICTs and the increasing prevalence of the internet, these criminal activities are significantly disrupting the global economy, national security, social stability, and individual interests. Although it is difficult to estimate the precise financial cost of cybercrime (Anderson et al., 2013 ; Anderson et al., 2019 ), statistical evidence from governments and industries indicates that the economic losses caused by cybercrime are extremely enormous and are still rising rapidly (McAfee, 2021 ).

Cybercrime is complicated in nature and involves many disciplines, including criminology, computer science, psychology, sociology, economics, geography, political science, and law, among others (Holt, 2017 ; Dupont and Holt, 2022 ; Payne, 2020 ). Computer science and cybersecurity efforts are primarily focused on applying technical approaches such as Intrusion Detection Systems (IDSs), Intrusion Prevention Systems (IPSs), firewalls, and anti-virus software to mitigate cyberattack threats (Kumar and Carley, 2016 ; Walters, 2015 ). These methods may help to some extent lessen the adverse impacts of cybercrime on both organisations and individuals. However, these technical solutions are largely unaware of the human and contextual factors that contribute to the issues, providing only reactive solutions, and are unable to keep up with the rapidly evolving modus operandi and emerging technologies (Clough, 2015 ; Neal, 2014 ). It is suggested that cybercrime is a complex social phenomenon driven by the compound interactions of underlying socioeconomic factors. Human and social factors play a substantial role in the formation of cybercrime agglomerations (Waldrop, 2016 ; Watters et al., 2012 ; Leukfeldt and Holt, 2019 ). They are also important aspects of cybercrime prevention and control (Dupont and Holt, 2022 ). The human factors influencing cybercrime have been the subject of an expanding body of sociological and psychological study in recent years. These studies, which covered cyberbullying, online harassment, identity theft, online fraud, malware infection, phishing, and other types of cybercrime, generally applied traditional criminological and psychological theories, such as routine activities theory, lifestyle-routine activities theory, self-control theory, and general strain theory, to explain the victimisation and offending of various cybercrimes (Bergmann et al., 2018 ; Mikkola et al., 2020 ; Ngo and Paternoster, 2011 ; Pratt et al., 2010 ; Williams, 2016 ). Results from these studies suggested that by altering criminal motivations and opportunity structures, individual factors (i.e., age, gender, ethnicity, education, socioeconomic status, and self-control) and situational factors (online activities, time spent online, risk exposure, deviant behaviours) may have an impact on cybercrime offence and victimisation. These findings advanced our knowledge in understanding the impact of technology on criminal behaviours, factors affecting the risk of cyber victimisation, and the applicability of traditional criminological theories to cybercrime (Holt and Bossler, 2014 ).

Cybercrime is a highly geographical phenomenon on a macro-level scale, with some countries accounting for a disproportionate amount of cybercrimes (Kigerl, 2012 ; Kigerl, 2016 ). This spatial heterogeneity is closely related to specific socioeconomic contexts (Kshetri, 2010 ). Academic efforts have been made to identify the clusters of high cybercrime countries and to explain the potential socioeconomic factors that led to the formation of these clusters. For example, Mezzour, Carley, and Carley ( 2014 ) found that Eastern European countries hosted a greater number of attacking computers due to their superior computing infrastructure and high levels of corruption. Similarly, Kumar and Carley ( 2016 ) found that higher levels of corruption and large internet bandwidth would favour attack origination. They also noted that countries with the greater gross domestic product (GDP) per capita and better ICT infrastructure were targeted more frequently. Meanwhile, Srivastava et al. ( 2020 ) pointed out that countries with better technology and economic capital were more likely to become the origins of cybercrime, but countries with better cybersecurity preparedness may reduce the frequency of the cybercrime originating within them. Moreover, Holt, Burruss, and Bossler ( 2018 ) suggested that nations with better technological infrastructure, greater political freedom, and fewer organised crime were more likely to report malware infections, while Overvest and Straathof ( 2015 ) suggested that the number of internet users, bandwidth, and economic ties were significantly related to cyberattack origin. Kigerl ( 2012 ) found that a higher unemployment rate and more internet users were linked to an increase in spam activities. However, these studies have tended to utilise a restricted range of predictor variables and only included certain aspects of cybercrime. Besides, most of the studies have been conducted at the national level, which could potentially hide many disparities within countries.

In this work, we construct a conceptual model to better represent the context from which cybercrime emerges, which is applied as a framework to analyse the underlying socioeconomic driving forces. A novel cybersecurity data set, the FireHOL IP blocklist, is adopted as a proxy to reflect the levels of cybercriminal activities within different areas. A set of social, economic, political, technological, and cybersecurity indicators is used as explanatory variables. Generalised linear models (GLMs) are used to quantify the effect of each factor on cybercrime, while structural equation modelling (SEM) is used to estimate the complex interactions among various factors and their direct and indirect effects on cybercrime.

Conceptual framework

We propose a conceptual framework for examining the driving forces of cybercrime by reviewing existing empirical literature and integrating different criminological theories. The conceptual framework includes five interrelated components: the social, economic, political, technological, and cybersecurity factors. The potential pathways by which each component may directly or indirectly influence cybercrime are illustrated in Fig. 1 .

The solid line indicates a direct effect, and a dashed line indicates indirect effect. H1–H5 refer to the five hypotheses, “+” indicates a positive effect, and “−” indicates a negative effect.

The social and economic factors depict the level of regional development, serving as the fundamental context in which cybercrime emerges. Given the intrinsic technological nature of cybercrime, global urbanisation, and the information technology revolution have promoted global connectivity and created unprecedented conditions and opportunities for cybercrime (UNODC, 2013 ). From the perspective of general strain theory, poverty, unemployment, income inequality, and other social disorders that are accompanied by social transformations could lead to cultures of materialism and stimulate motivations of cybercrime for illegal gains (Meke, 2012 ; Onuora et al., 2017 ). On the other hand, economically developed regions generally have superior ICT infrastructure, which can provide convenient and low-cost conditions for cybercriminals to commit crimes. High educational attainment is also likely to be associated with cybercrime, given that cybercrime usually requires some level of computer skills and IT knowledge (Holt and Schell, 2011 ; Asal et al., 2016 ). In general, better socioeconomic conditions are associated with more cybercriminal activities, which leads us to develop the first two hypotheses:

H1: Social factor is positively associated with cybercrime .

H2: Economic factor is positively associated with cybercrime .

The influence of political factors on cybercrime is mainly reflected in the regulation and intervention measures of governments in preventing and controlling cybercrime, such as legal system construction, government efficiency, control of corruption, and political stability. The offender’s decision to engage in illegal activity is a function of the expected probability of being arrested and convicted and the expected penalty if convicted (Ehrlich, 1996 ). As with traditional crimes, the lack of efficient social control and punishment mechanism will breed criminal behaviours. The deterrent effect of the legislation makes cybercriminals have to consider the consequences they need to bear. While the virtual and transnational nature of cyberspace makes it easier for perpetrators to avoid punishment, cybercrime can be deterred to some extent by increasing the severity of punishment and international law enforcement cooperation (Hall et al., 2020 ). On the other side, cybercriminals could seek protection through corrupt connections with the local institutional environment, which would weaken law enforcement operations and encourage cybercriminal activities (Hall et al., 2020 ; Lusthaus and Varese, 2021 ; Sutanrikulu et al., 2020 ). For instance, corruption in law enforcement authorities makes it hard for cybercriminals to be punished, while corruption in network operators or internet service providers (ISPs) makes it easier for cybercriminals to apply for malicious domain names or register fake websites. Some studies have shown that areas with high levels of corruption usually have more cybercriminal activities (Mezzour et al., 2014 ; Watters et al., 2012 ). Cybercrimes are typically attributed to political corruption, ineffective governance, institutional weakness, and weak rule of law across West Africa and East Europe (Asal et al., 2016 ). Therefore, we propose that:

H3: Political factor is negatively associated with cybercrime .

The technological environment, which is composed of communication conditions and underlying physical ICT infrastructure, serves as an essential medium through which cybercrime is committed. According to the rational choice theory, crime is the result of an individual’s rational consideration of the expected costs and benefits attached to their criminal activity (Mandelcorn et al., 2013 ; Brewer et al., 2019 ). Better internet infrastructure, greater internet penetration, and faster connection could facilitate cybercrimes by reducing crime costs, expanding opportunities, and increasing potential benefits. For example, in a majority of spam and DDoS attacks, cybercriminals often carry out large-scale coordinated attacks by sending remote commands to a set of compromised computers (also known as botnets). High-performance computers and high-bandwidth connectivity such as university, corporate, and government servers allow for more efficient attacks and could expand the scope of cybercrime, making them preferred by cybercriminals (Hoque et al., 2015 ; Van Eeten et al., 2010 ; Eslahi et al., 2012 ). We thus hypothesise that:

H4: Technological factor is positively related to cybercrime .

Cybersecurity preparedness reflects the capabilities and commitment of a country to prevent and combat cybercrime. According to the International Telecommunication Union (ITU), cybersecurity preparedness involves the legal, technical, organisation, capacity, and cooperation aspects (Bruggemann et al., 2022 ). Legal measures such as laws and regulations define what constitutes cybercrime and specify necessary procedures in the investigation, prosecution, and sanction of cybercrime, providing a basis for other measures. Technical measures refer to the technical capabilities to cope with cybersecurity risks and build cybersecurity resilience through national institutions and frameworks such as the Computer Incident Response Teams (CIRTs) or Computer Emergency Response Teams (CERTs). Organisation measures refer to the comprehensive strategies, policies, organisations, and coordination mechanisms for cybersecurity development. Capacity development reflects the research and development, awareness campaigns, training and education, and certified professionals and public agencies for cybersecurity capacity building. Cooperation measures refer to the collaboration and information sharing at the national, regional, and international levels, which is essential in addressing cybersecurity issues given the transnational nature of cybercrime. According to the general deterrence theory and routine activity theory of criminology (Leukfeldt and Holt, 2019 ; Hutchings and Hayes, 2009 ; Lianos and McGrath, 2018 ), cybersecurity preparedness serves as a deterrent or a guardianship of cybercrime. It is crucial in defending a country from external cybercrime as well as reducing cybercrime originating from within. Therefore, we hypothesise that:

H5: Cybersecurity preparedness is negatively associated with cybercrime .

The five hypotheses proposed in the conceptual model (Fig. 1 ) outline the direct effects of various contextual drivers on cybercrime. The social, economic, political, technological, and cybersecurity factors may interact in other ways, which could also have an indirect impact on cybercrime. Then, using a combination of two statistical methods and a set of explanatory covariates, we test the hypothesised pathways.

Cybercrime data

It is commonly acknowledged among cybercrime scholars that the lack of standardised legal definitions of cybercrime and valid, reliable official statistics makes it difficult to estimate the prevalence or incidence of cybercrime around the world (Holt and Bossler, 2015 ). Although in some countries, law enforcement agencies do collect data on cybercrime (e.g., police data and court judgement), there are inevitable under-reporting and under-recording issues with these official data (Holt and Bossler, 2015 ; Howell and Burruss, 2020 ). This has prompted some researchers to use alternative data sources to measure cybercrime, including social media, online forums, emails, and cybersecurity companies (Holt and Bossler, 2015 ). Among these data sources, technical data such as spam emails, honeypots, IDS/IPS or firewall logs, malicious domains/URLs, and IP addresses are often used as proxies for different aspects of cybercrime (Amin et al., 2021 ; Garg et al., 2013 ; Kigerl, 2012 ; Kigerl, 2016 ; Kigerl, 2021 ; Mezzour et al., 2014 ; Srivastava et al., 2020 ; Kshetri, 2010 ), accounting for a large proportion in the literature of macro-level cybercrime research. However, due to the anonymity and virtuality of cyberspace, cybercriminals are not restrained by national boundaries and could utilise compromised computers distributed around the world as a platform to commit cybercrime. Meanwhile, IP addresses can be faked or spoofed by using technologies such as proxy servers, anonymity networks, and virtual private networks (VPNs) to hide the true identity and location of cybercriminals (Holt and Bossler, 2015 ; Leukfeldt and Holt, 2019 ). As a result, the attribution of cybercriminal becomes extremely challenging and requires a high level of expertise and coordination from law enforcement agencies and cybersecurity teams (Lusthaus et al., 2020 ). Therefore, instead of capturing where cybercriminals reside in physical space, most studies using these technical data are measuring the possible locations where the cyberattacks or cybercrimes originate, even if part of them could be locations where cybercriminals choose to host their botnets or spam servers. Though there is partial support that certain types of cyberattacks originate from physically proximate IP addresses (Maimon et al., 2015 ), more elaborate and comprehensive research is lacking.

In this study, we used a novel cybersecurity data set, the IP addresses from FireHOL blocklist (FireHOL, 2021 ), as a proxy to measure cybercrime. The FireHOL IP blocklist is a composition of multiple sources of illegitimate or malicious IP addresses, which can be used on computer systems (i.e., servers, routers, and firewalls) to block access from and to these IPs. These IPs are related to certain types of cybercrime activities, including abuse, attacks, botnets, malware, command and control, and spam. We adopt FireHOL level 1 blocklist, which consists of ~2900 subnets and over 600 million unique IPs, with a minimum of false positives. The anonymous IPs, which are used by other parties to hide their true identities, such as open proxies, VPN providers, etc., were excluded from the analysis. Next, we applied an open-source IP geolocation database, IP2Location™ Lite, to map these unique IP addresses in specific geographic locations in the form of country/region/city and longitude/altitude pair. The location accuracy of the IP geolocation is high at the national and regional levels, with ~98% accuracy at the country level and 60% at the city level. In order to reduce uncertainty, we focused on the analysis at the state/region level. At last, we calculated the counts of unique IPs located within each subnational area to measure the global distribution of cybercrimes.

Although FireHOL IP blocklist has the same restrictions as other technical data, it was used in this study for several reasons. The basic function of IP addresses in the modern internet makes it an indispensable element in different phases of cybercrime, it is also the key ingredient of cybercrime attribution and digital evidence collection. As a result, an IP-based firewall is one of the most effective and commonly used preventive measures for cybersecurity defence. FireHOL IP blocklist has the advantage of global coverage and includes different cybercrime types. It dynamically collects cybercrime IPs from multiple sources around the world. Although it is difficult to determine whether the IPs in the blocklist are the real sources of cybercrime or come from infected machines, it does reflect the geographical distribution of the malicious IPs that are related to certain cybercrime activities. Besides, it provides a more fine-grained estimate of the subnational cybercrime geography than country-level statistics.

Explanatory variables

We adopted a broad set of explanatory variables to characterise the social, economic, political, technological, and cybersecurity conditions based on the conceptual model presented above (Fig. 1 ). The social environment is represented by population, the population aged 15–64, education index, nighttime light index, and human development index (HDI); The economic condition is measured by income index, GDP growth, Gini index, unemployment (% of the total labour force) and poverty rate; The political environment is measure by 5 dimensions of the World Governance Indicators (WGI), including control of corruption, government effectiveness, rule of law, political stability and absence of violence/terrorism, voice and accountability. The technological environment is reflected by the internet infrastructure (the number of internet data centres and internet exchange centres), internet users (% of the population), international bandwidth (per internet user), secure internet server (per 1 million people), and fixed broadband subscriptions (per 100 people). Moreover, we applied the five dimensions of the Global Cybersecurity Index (GCI) to assess the level of commitment among various nations to cybersecurity, including legal measures, technical measures, organisational measures, capacity development measures, cooperation measures, and one overall cybersecurity index (the sum of the 5 measures above). Population, income index, education index, HDI, nighttime light, and infrastructure data are collected at the subnational administrative level, while other variables are derived at the country level. Log transformations (base 10) were used to improve normality for variables with skewed distributions, including population, nighttime light, infrastructure, fixed broadband, secure internet server, and bandwidth. All variables were normalised for further analysis.

Generalised linear models (GLMs)

In this study, GLMs were used to assess the potential influence of various explanatory variables on cybercrime and to identify the most important factors. A GLM is an extension of a regular regression model that includes nonnormal response distributions and modelling functions (Faraway, 2016 ). GLM analyses were conducted at two scales: the global scale and the income group scale. All GLMs were built in R version 4.1.2 using the “glm” function of the “stats” package (R, Core Team, 2013 ), and a gaussian distribution is used as the link function. The Akaike information criterion (AIC), the determination coefficient ( R 2 ), and the significance level of the predictors ( p -value) are used to evaluate GLMs. The model with the lowest AIC and highest R 2 value is chosen as the optimal model. Variance inflation factors (VIFs) were calculated using the “car” package (Fox et al., 2012 ) to test for collinearity between quantitative explanatory variables prior to the GLM analysis. Variables with a VIF value greater than 10 (VIF > 10) were regarded as collinearity generators and were therefore excluded from further analysis. The relative contribution and coefficients of each GLM were plotted using the “GGally” package.

Structural equation modelling (SEM)

SEM was used to examine the causal relationships within the networks of interacting factors, thereby distinguishing the direct from indirect drivers of cybercrime. SEM is a powerful, multivariate technique found increasingly in scientific investigations to test and evaluate multivariate causal relationships (Fan et al., 2016 ). SEM differs from other modelling approaches in that it tests both the direct and indirect effects on pre-assumed causal relationships. The following fit indices were considered to evaluate model adequacy: (a) root mean square error of approximation (RMSEA), which is a “badness of fit” index in which 0 indicates a perfect fit while higher values indicate a lack of fit; (b) standardised root mean square residual (SRMR), which is similar to RMSEA and should be less than 0.09 for good model fit; (c) comparative fit index (CFI), which represents the amount of variance that has been accounted for in a covariance matrix ranging from 0.0 to 1.0, with a higher CFI value indicating better model fit; (d) Tucker–Lewis index (TLI), which is a non-normed fit index (NNFI) that proposes a fit index independent of sample size. In this study, SEM analysis was conducted using AMOS (Arbuckle, 2011 ).

Spatial distribution of cybercrime IPs

We mapped the subnational distribution of cybercrime IPs globally, which reveals significant spatial variability (see Fig. 2 ). On a global scale, most cybercrime IPs were located in North America, Central and Eastern Europe, East Asia, India, and eastern Australia. Meanwhile, areas with low numbers of cybercrime IPs were primarily found in large parts of Africa except for South Africa, western and northern parts of South America, Central America, some regions of the Middle East, southern parts of Central Asia, and some regions of Southeast Asia. On a continental scale, we found that the number of cybercrime IPs increased gradually from Africa to Europe. The two continents with the most cybercrime IPs were North America and Europe, with North America showing more variations. This trend seems to be closely associated with the regional socioeconomic development level. To further investigate this relationship, we grouped the subnational regions by income level according to the World Bank classification rules. We found a more evident pattern, with high-income regions hosting the majority of cybercrime IPs and lower-middle-income regions hosting the least.

a Number of cybercrime IPs at the subnational level. b Log-transformed cybercrime IP count by continent: Africa (AF), Asia/Oceania (AS/OC), South America (SA), North America (NA) and Europe (EU). c Log-transformed cybercrime IP count by income group: low-income (LI), lower-middle-income (LMI), upper-middle-income (UMI) and high-income (HI) groups. The centre line, boxes, and whiskers show the means, 1 standard error (SE), and 95% confidence interval (CI), respectively.

Major factors influencing cybercrime

GLMs were built based on the 5 categories of 26 representative influential variables identified in the conceptual framework. After excluding 8 collinear variables (i.e., government effectiveness, rule of law, HDI, and 5 cybersecurity measures) and 7 nonsignificant variables (GDP growth, unemployment, poverty, political stability, voice and accountability, bandwidth, and internet users), the global scale GLM model includes 11 variables with an R 2 value of 0.82. Figure 3 shows the relative contribution of each predictor variable to the model. Globally, the social and technological factors contribute most to the model, with relative contribution rates of 53.4% and 30.1%, respectively. Infrastructure alone explains up to 18.1% of the model variance in cybercrimes ( R 2 to 0.504). However, the inclusion of the population and education index improves the explanation of model variance by 18.3% and 28.5%, respectively ( R 2 to 0.596 and 0.766). This is also the case with GLMs of different income groups, indicating that despite the main effects of technological factors, the inclusion of a broad set of socioeconomic factors significantly improves the accuracy of models that attempt to quantify the driving forces of cybercrime.

Relative contribution of predictor variables to cybercrime.

When assessed by income group, we noted that although the social and technological factors were the most important factors in explaining cybercrime, the contribution of each variable varies by income group. For example, the contribution of the income index decreases gradually from low-income regions to wealthier regions, while the Gini index is more significant in upper-middle regions and high-income regions than in low-income regions and lower-middle-income regions. Fixed broadband subscriptions contributed the most in low-income regions and the least in high-income regions. Additionally, cybersecurity preparedness has a greater influence on low-income and lower-middle-income regions.

Estimated effect of factors on cybercrime

The coefficient values in Fig. 4 represent effect sizes from the GLMs for the relationship between cybercrime and the five categories of contextual factors. At the global scale, cybercrime is positively correlated with social, economic, and technological factors, suggesting that most cybercrimes are launched in regions with a higher population, higher urbanisation, better educational and economic conditions, and, most importantly, improved internet infrastructure and communication conditions. By contrast, cybercrime is negatively related to political and cybersecurity factors, indicating that the control of corruption and the commitment to cybersecurity show certain inhibitory effects on cybercrime.

The coefficient values are represented as dots, significant variables are represented as filled dots, nonsignificant variables are represented as hollow dots, and bars represent 95% CIs.

From the perspective of income groups, the ways contextual factors affect cybercrime remain basically consistent with the global results, but subtle differences are observed. In low-income countries, the influence of the income index on cybercrime is the strongest, and cybercrime is significantly associated with a higher income index, higher education index, better infrastructure, and higher fixed broadband subscriptions. This pattern may indicate that in low-income countries, wealthier areas tend to have more cybercrimes due to the existence of better communication conditions in these areas. However, in high-income countries, where the internet is universally available, the roles of income index and fixed broadband subscriptions gradually weaken. In contrast, the effects of the Gini index and education are stronger in wealthier countries, indicating that economic inequality and education in these countries can be important drivers of cybercrime. Moreover, the control of corruption is negatively related to cybercrime in lower-middle, upper-middle, and high-income regions.

Pathways of factors for cybercrime

To understand the intricate interactions among different predictors, we perform SEM based on the conceptual model. The SEM model is composed of five latent variables, representing the social, economic, political, technological, and cybersecurity context, and each latent variable has five components reflected by the explanatory variables. Overall SEM fit is assessed, showing a good fit (CFI = 0.917, TLI = 0.899, SRMR = 0.058). SEM confirms many of the hypotheses in the conceptual model, and all relationships are statistically significant. Fig. 5 shows the results of SEM.

Black arrows indicate a positive effect, red arrows indicate a negative effect, and values on the straight arrows between variables represent the standardised path coefficients.

According to the SEM, all the hypotheses are tested and supported. Specifically, social, economic, and technological factors have direct positive effects on cybercrime (standardised path coefficients of direct effect are 0.03, 0.10, and 0.61, respectively), indicating that when social, economic, and technological factors go up by 1 standard deviation, cybercrime goes up by 0.03, 0.10, and 0.61 standard deviations, respectively. By contrast, the political and cybersecurity factors have direct negative effects on cybercrime (standardised path coefficients of direct effect are −0.22 and −0.07, respectively), indicating that 1 standard deviation rise in political and cybersecurity factors are associated with 0.22 and 0.07 standard deviations decrease of cybercrime, respectively. It is worth noting that although the direct effects of social and economic factors on cybercrimes are relatively small, their indirect effects on cybercrime through the mediation of technological and political factors are non-negligible.

In sum, SEM quantifies the direct and indirect effects of social, economic, political, technological, and cybersecurity factors on cybercrime, consistent with the hypotheses outlined in the conceptual model. More importantly, the results suggest that even though cybercrimes are primarily determined by technological factors, the direct and indirect effects of underlying social, economic, political, and cybersecurity also play significant roles. This suggests that the technological factor is a necessary but not sufficient condition for the occurrence of cybercrime.

In the current study, we mapped the global subnational distribution of cybercrimes based on a novel cybersecurity data set, the FireHOL IP blocklist. Given the widespread difficulty in obtaining cybercrime data, the data sources used in this study could provide an alternative measure of the subnational cybercrime level on a global scale. Compared to country-level studies (Amin et al., 2021 ; Garg et al., 2013 ; Goel and Nelson, 2009 ; Solano and Peinado, 2017 ; Sutanrikulu et al., 2020 ), the results present a more fine-grained view of the spatial distribution of cybercrime. The map reveals high spatial variability of cybercrime between and within countries, which appears to be closely related to local socioeconomic development status.

To recognise the driving forces behind cybercrime, we proposed a theoretical framework that encompasses the social, economic, political, technological, and cybersecurity factors influencing cybercrime, drawing on existing theoretical and empirical research. On this basis, we used GLMs to identify the major factors and their contributions to cybercrime and SEM to quantify the direct and indirect effects of these driving forces. The GLM results show that using technological factors alone as explanatory variables is insufficient to account for cybercrime, and the inclusion of a broad suite of social, economic, political, technological, and cybersecurity factors can remarkably improve model performance. Global scale modelling indicates that cybercrime is closely associated with socioeconomic and internet development, as developed regions have more available computers and better communication conditions that facilitate the implementation of cybercrime. Some studies have argued that wealthier areas might have fewer incentives for cybercrime, while poorer areas could benefit more from cybercrime activities (Ki et al., 2006 ; Kigerl, 2012 ; Kshetri, 2010 ). However, our study shows that the technological factors constituted by the internet infrastructure and communication conditions are necessary for the production of cybercrime, rendering wealthier areas more convenient for committing cybercrime.

Meanwhile, the GLMs of the 4 income groups demonstrate important differential impacts of the explanatory variables on cybercrime. For example, in low-income countries, where the overall internet penetration rate is low, cybercrime originates mainly in more developed areas with better internet infrastructure, higher internet penetration, and higher education levels. A typical example is the “Yahoo Boys” in Nigeria, referring to young Nigerians engaged in cyber fraud through Yahoo mail, mostly well-educated undergraduates with digital skills (Lazarus and Okolorie, 2019 ). A range of factors, such as a high rate of unemployment, a lack of legitimate economic opportunities, a prevalence of cybercrime subculture, a lack of strong cybercrime laws, and a high level of corruption, have motivated them to obtain illegal wealth through cybercrime. In contrast, cybercrime in high-income regions originates in areas with a high Gini index and a high education level. One possible explanation for this finding may be that well-educated individuals who live in countries with a high Gini index are paid less for their skills than their counterparts, which motivates them to engage in cybercrimes to improve their lives.

Encouragingly, both the GLM and SEM results suggest that political factors and cybersecurity preparedness can mitigate the incidence of cybercrime to some extent, in agreement with the hypotheses. Though previous country-level studies suggest that countries facing more cybersecurity threats tend to have a high level of cybersecurity preparedness (Makridis and Smeets, 2019 ; Calderaro and Craig, 2020 ), our results indicate that cybersecurity preparedness could in turn reduce cybercrimes that originate from a country. This emphasises the importance of government intervention and cybersecurity capacity building. The necessary intervening measures may include the enactment and enforcement of laws, regulation of telecommunication operators and internet service providers (ISPs), strengthening of strike force by security and judicial departments, and improvement of cybersecurity capacity. Given the interconnectedness of cyberspace and the borderless nature of cybercrime, it must be recognised that cybersecurity is not a problem that can be solved by any single country. Thus, enhancing international cooperation in legal, technical, organisational, and capacity aspects of cybersecurity becomes an essential way to tackle cybersecurity challenges.

As presented through SEM, technological factors are closely associated with the development of socioeconomic development and serve as a mediator between socio-economic conditions and cybercrime. In the past decades, ICTs have developed unevenly across different parts of the world due to a range of geographic, socioeconomic, and demographic factors, which has led to the global digital divide (Pick and Azari, 2008 ). The disparities in internet access in different regions have largely determined the spatial patterns of cybercrime. Currently, developing countries (especially those within Asia, Africa, and Latin America) are the fastest-growing regions in terms of ICT infrastructure and internet penetration (Pandita, 2017 ). However, even in developed countries, the progress of technological innovation has outpaced the establishment of legal regulations, national institutions and frameworks, policies and strategies, and other mechanisms that could help manage the new challenges (Bastion and Mukku, 2020 ). Many developing countries are facing difficulties in combating cybercrime due to a lack of adequate financial and human resources, legal and regulatory frameworks, and technical and institutional capacities, providing a fertile ground for cybercrime activities. In this vein, it is extremely urgent and necessary to enhance the cybersecurity capacities of developing countries and engage them in the international cooperation of cybersecurity, ensuring that they can maximize the socio-economic benefits of technological development instead of being harmed by it.

Cybercrime is a sophisticated social phenomenon rooted in deep and comprehensive geographical and socioeconomic causes. This study offers an alternative perspective in solving cybersecurity problems instead of pure technical measures. We believe that improvements in cybersecurity require not only technological, legal, regulatory, and policing measures but also broader approaches that address the underlying social, economic, and political issues that influence cybercrime. While the results presented in this study are preliminary, we hope that this work will provide an extensible framework that can be expanded for future studies to investigate the driving forces of cybercrime.

However, our study has several limitations due to the disadvantages of data. First and foremost, the geo-localisation of cybercrimes or cybercriminals remains a major challenge for cybercrime research. Although the FireHOL IP blocklist has the potential to measure global cybercrime at a high spatial resolution, IP-based measures may not accurately capture the true locations of cybercriminals, as they may simply exploit places with better ICT infrastructure. Therefore, caution should be exercised in interpreting the associations between cybercrime and socioeconomic factors. Future studies combining survey data, police and court judgement data, and cybercrime attribution techniques are needed to further validate the accuracy and validity of IP-based technical data in measuring the geography of cybercrime and gain a deeper understanding of the driving forces of cybercrime. Besides, COVID-19 has greatly changed the way we live and work, and many studies have suggested that the pandemic has increased the frequency of cybercrimes within the context of economic recession, high unemployment, accelerated digital transformation, and unprecedented uncertainty (Lallie et al., 2021 ; Eian et al., 2020 ; Pranggono and Arabo, 2021 ). Unfortunately, the blocklist data cannot well capture this dynamic due to a lack of temporal attributes. Furthermore, different types of cybercrime can be influenced by different mechanisms. We use the total amount of all types of cybercrime IPs instead of looking into a specific type of cybercrime, given that such segmentation may result in data sparsity for some groups. Future studies are needed to determine how different categories of cybercrimes are affected by socioeconomic factors. At last, micro-level individual and behaviour characteristics and more fine-grained explanatory variables should be included to better understand cybercrime.

Data availability

The FireHOL IP lists data are publicly available at the FireHOL website ( https://iplists.firehol.org/ and https://github.com/firehol/blocklist-ipsets ); population, education index, income index, HDI, and subnational regions data are available from Global Data Lab ( https://globaldatalab.org ); nighttime light data are available from the Earth Observation Group ( https://eogdata.mines.edu/download_dnb_composites.html ); Population aged 15–64, Gini index, GDP growth, unemployment, poverty rate, control of corruption, government effectiveness, rule of law, political stability and absence of violence/terrorism, and voice and accountability, are obtained from World Bank ( https://databank.worldbank.org/home.aspx ), the internet users, international bandwidth, secure internet server, and fixed broadband subscriptions are available from International Telecommunication Union (ITU) ( https://www.itu.int/itu-d/sites/statistics ); the internet infrastructure are collected from TeleGeography ( https://www.internetexchangemap.com ) and the World Data Centers Database ( https://datacente.rs ); the legal measures, technical measures, organisational measures, capacity development, cooperation measures and overall cybersecurity index were obtained from the Global Cybersecurity Index (GCI) of the ITU ( https://www.itu.int/en/ITU-D/Cybersecurity/Pages/global-cybersecurity-index.aspx ).

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Acknowledgements

This research was funded by the National Key Research and Development Project of China, grant number 2020YFB1806500 and the Key Research Program of the Chinese Academy of Sciences, grant number ZDRW-XH-2021-3. We thank Yushu Qian, Ying Liu, Qinghua Tan for providing valuable suggestions.

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DJ, QQG and CDG designed the research; SC, FYD, DJ, SZZ and MMH performed the research; SC, FYD and JPD analysed the data; SC, FYD, DJ and MMH wrote the first draft of the paper; JPD, SZZ, QQG, CDG and DJ gave useful edits, comments and suggestions to this work.

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Chen, S., Hao, M., Ding, F. et al. Exploring the global geography of cybercrime and its driving forces. Humanit Soc Sci Commun 10 , 71 (2023). https://doi.org/10.1057/s41599-023-01560-x

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Research on cybercrime victimization is relatively diversified; however, no bibliometric study has been found to introduce the panorama of this subject. The current study aims to address this research gap by performing a bibliometric analysis of 387 Social Science Citation Index articles relevant to cybercrime victimization from Web of Science database during the period of 2010–2020. The purpose of the article is to examine the research trend and distribution of publications by five main fields, including time, productive authors, prominent sources, active institutions, and leading countries/regions. Furthermore, this study aims to determine the global collaborations and current gaps in research of cybercrime victimization. Findings indicated the decidedly upward trend of publications in the given period. The USA and its authors and institutions were likely to connect widely and took a crucial position in research of cybercrime victimization. Cyberbullying was identified as the most concerned issue over the years and cyber interpersonal crimes had the large number of research comparing to cyber-dependent crimes. Future research is suggested to concern more about sample of the elder and collect data in different countries which are not only European countries or the USA. Cross-nation research in less popular continents in research map was recommended to be conducted more. This paper contributed an overview of scholarly status of cybercrime victimization through statistical evidence and visual findings; assisted researchers to optimize their own research direction; and supported authors and institutions to build strategies for research collaboration.

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Introduction

To date, the debate of cybercrime definition has been controversial which is considered as one of the five areas of cyber criminology (Ngo and Jaishankar 2017 ; Drew 2020 ). Footnote 1 Several terms are used to illustrate ‘cybercrime’, such as ‘high-tech crime’ (Insa 2007 ), ‘computer crime’ (Choi 2008 ; Skinner and Fream 1997 ), ‘digital crime’ (Gogolin 2010 ), or ‘virtual crime’ (Brenner 2001 ). ‘Cybercrime’, however, has been the most popular in the public parlance (Wall 2004 ). A propensity considers crime directly against computer as cybercrime, while other tendency asserts that any crime committed via internet or related to a computer is cybercrime (Marsh and Melville 2008 ; Wall 2004 ). Hence, there is a distinction between ‘true cybercrime’ or ‘high-tech’ cybercrime and ‘low-tech’ cybercrime (Wagen and Pieters 2020 ). Council of Europe defines ‘any criminal offense committed against or with the help of a computer network’ as cybercrime (Abdullah and Jahan 2020 , p. 90). Despite different approaches, cybercrime generally includes not only new types of crimes which have just occurred after the invention of computer and internet (Holt and Bossler 2014 ; Drew 2020 ) but also traditional types of crimes which took the advantages of information communication technology (ICT) as vehicle for illegal behaviors (Luong 2021 ; Nguyen and Luong 2020 ; Luong et al. 2019 ). Two main cybercrime categories identified, respectively, are cyber-dependent crime (hacking, malware, denial of service attacks) and cyber-enable crime (phishing, identity theft, cyber romance scam, online shopping fraud). Nevertheless, there are several different classifications of cybercrime such as cybercrime against certain individuals, groups of individuals, computer networks, computer users, critical infrastructures, virtual entities (Wagen and Pieters 2020 ); cyber-trespass, cyber-deceptions, cyber-pornography, and cyber-violence (Wall 2001 ).

Due to the common prevalence of cybercrime, the increasing threats of cybercrime victimization are obviously serious. Cybercrime victimization has become a crucial research subfield in recent years (Wagen and Pieters 2020 ). It is difficult to differ “forms of online victimization” and “acts that actually constitute a crime”, then it is usual for researchers to focus less on perspective of criminal law and consider any negative experiences online as cybercrime (Näsi et al. 2015 , p. 2). It was likely to lead to practical gaps between theory and practice in terms of investigating the nexus of offender and victims on cyberspace. In the light of literature review, numerous specific aspects of cybercrime victimization were investigated by questionnaire surveys or interview survey such as the prevalence of cybercrime victimization (Näsi et al. 2015 ; Whitty and Buchanan 2012 ); causes and predictors of cybercrime victimization (Abdullah and Jahan 2020 ; Algarni et al. 2017 ; Ilievski 2016 ; Jahankhani 2013 ; Kirwan et al. 2018 ; Näsi et al. 2015 ; Reyns et al. 2019 ; Saad et al. 2018 ); and the relationship between social networking sites (SNS) and cybercrime victimization (Das and Sahoo 2011 ; Algarni et al. 2017 ; Benson et al. 2015 ; Seng et al. 2018 ). To some extent, therefore, the current study examines cybercrime victimization in the large scale, referring to any negative experiences on cyberspace or computer systems. Nevertheless, no bibliometric analysis was found to show the research trend and general landscape of this domain.

Bibliometric is a kind of statistical analysis which uses information in a database to provide the depth insight into the development of a specified area (Leung et al. 2017 ). The present study aims to address this research gap by providing a bibliometric review of the relevant SSCI articles in WoS database during the period of 2010–2020. The pattern of publications, the productivity of main elements (authors, journals, institutions, and countries/regions), statistic of citations, classification of key terms, research gaps, and other collaborations will be presented and discussed in section four and five after reviewing literatures and presenting our methods conducted. This article contributes an overview of research achievements pertaining to cybercrime victimization in the given period through statistical evidence and visual findings; assists researchers to perceive clearly about the key positions in research maps of this field, and obtain more suggestions to develop their own research direction.

Literature review

• Cybercrime victimization

Cybercrime victimization may exist in two levels including institutional and individual level (Näsi et al. 2015 ). For the former, victim is governments, institutions, or corporations, whereas for the latter, victim is a specific individual (Näsi et al. 2015 ). A wide range of previous studies concerned about individual level of victim and applied Lifestyle Exposure Theory (LET), Routine Activity Theory (RAT) and General Theory of Crime to explain cybercrime victimization (Choi 2008 ; Holt and Bossler 2009 ; Ngo and Paternoster 2011 ). Basing on these theories, situational and individual factors were supposed to play an important role in understanding cybercrime victimization (Choi 2008 ; Van Wilsem 2013 ). However, there was another argument that situational and individual factors did not predict cybercrime victimization (Ngo and Paternoster 2011 ; Wagen and Pieters 2020 ). Overall, most of those studies just focused only one distinctive kind of cybercrime such as computer viruses, malware infection, phishing, cyberbullying, online harassment, online defamation, identity theft, cyberstalking, online sexual solicitation, cyber romance scams or online consumer fraud. Referring to results of the prior research, some supported for the applicability of mentioned theories but other did not share the same viewpoint (Leukfeldt and Yar 2016 ). It was hard to evaluate the effect of LET or RAT for explanation of cybercrime victimization because the nature of examined cybercrime were different (Leukfeldt and Holt 2020 ; Leukfeldt and Yar 2016 ).

Previous research determined that cybercrime victimization was more common in younger group compared to older group because the young is the most active online user (Näsi et al. 2015 ; Oksanen and Keipi 2013 ) and males tended to become victims of cybercrime more than females in general (Näsi et al. 2015 ). However, findings might be different in research which concerned specific types of cybercrime. Women were more likely to be victims of the online romance scam (Whitty and Buchanan 2012 ) and sexual harassment (Näsi et al. 2015 ), while men recorded higher rate of victimization of cyber-violence and defamation. Other demographic factors were also examined such as living areas (Näsi et al. 2015 ), education (Oksanen and Keipi 2013 ; Saad et al. 2018 ) and economic status (Oksanen and Keipi 2013 ; Saad et al. 2018 ). Furthermore, several prior studies focus on the association of psychological factors and cybercrime victimization, including awareness and perception (Ariola et al. 2018 ; Saridakis et al. 2016 ), personality (Kirwan et al. 2018 ; Orchard et al. 2014 ; Parrish et al. 2009 ), self-control (Ilievski 2016 ; Ngo and Paternoster 2011 ; Reyns et al. 2019 ), fear of cybercrime (Lee et al. 2019 ), online behaviors (Al-Nemrat and Benzaïd 2015 ; Saridakis et al. 2016 ). Psychological factors were assumed to have effects on cybercrime victimization at distinctive levels.

Another perspective which was much concerned by researchers was the relationship between cybercrime victimization and SNS. SNS has been a fertile land for cybercriminals due to the plenty of personal information shared, lack of guard, the availability of communication channels (Seng et al. 2018 ), and the networked nature of social media (Vishwanath 2015 ). When users disclosed their personal information, they turned themselves into prey for predators in cyberspace. Seng et al. ( 2018 ) did research to understand impact factors on user’s decision to react and click on suspicious posts or links on Facebook. The findings indicated that participants’ interactions with shared contents on SNS were affected by their relationship with author of those contents; they often ignored the location of shared posts; several warning signals of suspicious posts were not concerned. Additionally, Vishwanath ( 2015 ) indicated factors that led users to fall victims on the SNS; Algarni et al. ( 2017 ) investigated users’ susceptibility to social engineering victimization on Facebook; and Kirwan et al. ( 2018 ) determined risk factors resulting in falling victims of SNS scam.

Bibliometric of cybercrime victimization

“Bibliometric” is a term which was coined by Pritchard in 1969 and a useful method which structures, quantifies bibliometric information to indicate the factors constituting the scientific research within a specific field (Serafin et al. 2019 ). Bibliometric method relies on some basic types of analysis, namely co-authorship, co-occurrence, citation, co-citation, and bibliographic coupling. This method was employed to various research domains such as criminology (Alalehto and Persson 2013 ), criminal law (Jamshed et al. 2020 ), marketing communication (Kim et al. 2019 ), social media (Chen et al. 2019 ; Gan and Wang 2014 ; Leung et al. 2017 ; Li et al. 2017 ; You et al. 2014 ; Zyoud et al. 2018 ), communication (Feeley 2008 ), advertising (Pasadeos 1985 ), education (Martí-Parreño et al. 2016 ).

Also, there are more and more scholars preferring to use bibliometric analysis on cyberspace-related subject such as: cyber behaviors (Serafin et al. 2019 ), cybersecurity (Cojocaru and Cojocaru 2019 ), cyber parental control (Altarturi et al. 2020 ). Serafin et al. ( 2019 ) accessed the Scopus database to perform a bibliometric analysis of cyber behavior. All documents were published by four journals: Cyberpsychology, Behavior and Social Networking (ISSN: 21522723), Cyberpsychology and Behavior (ISSN: 10949313) , Computers in Human Behavior (ISSN: 07475632) and Human–Computer Interaction (ISSN: 07370024), in duration of 2000–2018. Findings indicated the use of Facebook and other social media was the most common in research during this period, while psychological matters were less concerned (Serafin et al. 2019 ). Cojocaru and Cojocaru ( 2019 ) examined the research status of cybersecurity in the Republic of Moldavo, then made a comparison with the Eastern Europe countries’ status. This study employed bibliometric analysis of publications from three data sources: National Bibliometric Instrument (database from Republic of Moldavo), Scopus Elsevier and WoS. The Republic of Moldavo had the moderate number of scientific publications on cybersecurity; Russian Federation, Poland, Romania, Czech Republic, and Ukraine were the leading countries in Eastern Europe area (Cojocaru and Cojocaru 2019 ). Altarturi et al. ( 2020 ) was interested in bibliometric analysis of cyber parental control, basing on publications between 2000 and 2019 in Scopus and WoS. This research identified some most used keywords including ‘cyberbullying’, ‘bullying’, ‘adolescents’ and ‘adolescence’, showing their crucial position in the domain of cyber parental control (Altarturi et al. 2020 ). ‘Cyber victimization’ and ‘victimization’ were also mentioned as the common keywords by Altarturi et al. ( 2020 ). Prior research much focus on how to protect children from cyberbullying. Besides, four online threats for children were determined: content, contact, conduct and commercial threats (Altarturi et al. 2020 ).

Generally, it has been recorded several published bibliometric analyses of cyber-related issues but remained a lack of bibliometric research targeting cybercrime victimization. Thus, the present study attempts to fill this gap, reviewing the achievements of existed publications as well as updating the research trend in this field.

In detail, our current study aims to address four research questions (RQs):

What is overall distribution of publication based on year, institutions and countries, sources, and authors in cybercrime victimization?

Which are the topmost cited publications in terms of cybercrime victimization?

Who are the top co-authorships among authors, institutions, and countries in research cybercrime victimization?

What are top keywords, co-occurrences and research gaps in the field of cybercrime victimization?

Data collection procedure

Currently, among specific approaches in cybercrime’s fileds, WoS is “one of the largest and comprehensive bibliographic data covering multidisciplinary areas” (Zyoud et al. 2018 , p. 2). This paper retrieved data from the SSCI by searching publications of cybercrime victimization on WoS database to examine the growth of publication; top keywords; popular topics; research gaps; and top influential authors, institutions, countries, and journals in the academic community.

This paper employed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for data collection procedure. For timeline, we preferred to search between 2010 and 2020 on the WoS system with two main reasons. First, when the official update of the 2009 PRISMA Statement had ready upgraded with the specific guidelines and stable techniques, we consider beginning since 2010 that is timely to test. Secondly, although there are several publications from the early of 2021 to collect by the WoS, its updated articles will be continued until the end of the year. Therefore, we only searched until the end of 2020 to ensure the full updates.

To identify publications on cybercrime victimization, the study accessed WoS and used two keywords for searching: ‘cybercrime victimization’ or ‘cyber victimization’ after testing and looking for some terminology-related topics. Accordingly, the paper applied a combination of many other searching terms besides two selected words such as “online victimization”, “victim of cybercrime”, “phishing victimization”, “online romance victimization”, “cyberstalking victim”, “interpersonal cybercrime victimization”, or “sexting victimization”, the results, however, were not really appropriate. A lot of papers did not contain search keywords in their titles, abstracts, keywords and were not relavant to study topic. After searching with many different terms and comparing the results, the current study selected the two search terms for the most appropriate articles. The query result consisted of 962 documents. Basing on the result from preliminary searching, retrieved publications were refined automatically on WoS by criteria of timespan, document types, language, research areas, and WoS Index as presented in Table 1 . Accordingly, the criteria for automatic filter process were basic information of an articles and classified clearly in WoS system so the results reached high accuracy. The refined results are 473 articles.

After automatic filters, file of data was converted to Microsoft Excel 2016 for screening. The present study examined titles and abstracts of 473 articles to assess the eligibility of each publication according to the relevance with given topic. There are 387 articles are eligible,while 86 irrelevant publications were excluded.

Data analysis

Prior to data analysis, the raw data were cleaned in Microsoft Excel 2016. Different forms of the same author’s name were corrected for consistency, for example “Zhou, Zong-Kui” and “Zhou Zongkui”, “Van Cleemput, Katrien” and “Van Cleemput, K.”, “Williams, Matthew L.” and “Williams, Matthew”. Similarly, different keywords (single/plural or synonyms) used for the same concept were identified and standardized such as “victimization” and “victimisation”; “adolescent” and “adolescents”; “cyber bullying”, “cyber-bullying” and “cyberbullying”; “routine activity theory” and “routine activities theory”.

The data were processed by Microsoft Excel 2016 and VOS Viewer version 1.6.16; then it was analyzed according to three main aspects. First, descriptive statistic provided evidence for yearly distribution and growth trend of publications, frequency counts of citations, the influential authors, the predominant journals, the top institutions and countries/territories, most-cited publications. Second, co-authorship and co-occurrence analysis were constructed and visualized by VOS Viewer version 1.6.16 to explore the network collaborations. Finally, the current study also investigated research topics through content analysis of keywords. The authors’ keywords were classified into 15 themes, including: #1 cybercrime; #2 sample and demographic factors; #3 location; #4 theory; #5 methodology; #6 technology, platforms and related others; #7 psychology and mental health; #8 physical health; #9 family; #10 school; #11 society; #12 crimes and deviant behaviors; #13 victim; #14 prevention and intervention; and #15 others. Besides, the study also added other keywords from titles and abstracts basing on these themes, then indicated aspects examined in previous research.

In this section, all findings corresponding with four research questions identified at the ouset of this study would be illustrated (Fig.  1 ).

PRISMA diagram depicts data collection from WoS database

Distribution of publication

Distribution by year, institutions and countries.

Basing on retrieved data, it was witnessed an increasing trend of articles relevant to cybercrime victimization in SSCI list during the time of 2010–2020 but it had slight fluctuations in each year as shown in Fig.  2 . The total number of articles over this time was 387 items, which were broken into two sub-periods: 2010–2014 and 2015–2020. It is evident that the latter period demonstrated the superiority of the rate of articles (79.33%) compared to the previous period (20.67%). The yearly quantity of publications in this research subject was fewer than forty before 2015. Research of cybercrime victimization reached a noticeable development in 2016 with over fifty publications, remained the large number of publications in the following years and peaked at 60 items in 2018.

Annual distribution of publications

Distribution by institutions and countries

Table 2 shows the top contributing institutions according to the quantity of publications related to cybercrime victimization. Of the top institutions, four universities were from the USA, two ones were from Spain, two institutions were from Australia and the rest ones were from Czech Republic, Belgium, Greece, and Austria. Specifically, Masaryk University (17 documents) became the most productive publishing institution, closely followed by Michigan State University (16 documents). The third and fourth places were University of Antwerp (13 documents) and Weber State University (10 documents). Accordingly, the institutions from The USA and Europe occupied the vast majority.

In Table 2 , University of Seville (total citations: 495, average citations: 70.71) ranked first and University of Cordoba (total citations: 484, average citations: 60.50) stayed at the second place in both total citations and average citations.

Referring to distribution of publications by countries, there were 45 countries in database contributing to the literature of cybercrime victimization. The USA recorded the highest quantity of papers, creating an overwhelming difference from other countries (159 documents) as illustrated in Fig.  3 . Of the top productive countries, eight European countries which achieved total of 173 publications were England (39 documents), Spain (34 documents), Germany (22 documents), Netherlands (18 documents), Italy (17 documents) and Czech Republic (17 documents), Belgium (14 documents), Greece (12 documents). Australia ranked the fourth point (32 documents), followed by Canada (30 documents). One Asian country which came out seventh place, at the same position with Netherlands was China (18 documents).

Top productive countries based on the number of publications

Distribution by sources

Table 3 enumerates the top leading journals in the number of publications relevant to cybercrime victimization. The total publications of the first ranking journal— Computers in Human Behavior were 56, over twice as higher as the second raking journal— Cyberpsychology, Behavior and Social Networking (24 articles). Most of these journals have had long publishing history, starting their publications before 2000. Only three journals launched after 2000, consisting of Journal of School Violence (2002), Cyberpsychology: Journal of Psychosocial Research on Cyberspace (2007) and Frontiers in Psychology (2010). Besides, it is remarked that one third of the top journals focuses on youth related issues: Journal of Youth and Adolescence , Journal of Adolescence, School Psychology International and Journal of School Violence .

In Table 3 , relating to total citations, Computers in Human Behavior remained the first position with 2055 citations. Journal of Youth and Adolescence had total 1285 citations, ranked second and followed by Aggressive Behavior with 661 citations. In terms of average citations per documents, an article of Journal of Youth and Adolescence was cited 67.63 times in average, much higher than average citations of one in Computers in Human Behavior (36.70 times). The other journals which achieved the high number of average citations per document were School Psychology International (59.00 times), Journal of Adolescence (44.83 times) and Aggressive Behavior (44.07 times).

Distribution by authors

Table 4 displays ten productive authors based on article count; total citations of each author and their average citations per document are also included. Michelle F. Wright from Pennsylvania State University ranked first with twenty publications, twice as higher as the second positions, Thomas J. Holt (10 articles) from Michigan State University and Bradford W. Reyns (10 articles) from Weber State University. Rosario Ortega-Ruiz from University of Cordoba stayed at the third place in terms of total publications but the first place in aspect of total citations (483 citations) and the average citations (60.38 times).

Of the most productive authors based on total publications, there were three authors from universities in the USA; one from the university in Canada (Brett Holfeld); the others were from institutions in Euro, including Spain (Rosario Ortega-Ruiz), Greece (Constantinos M. Kokkinos) and Belgium (Heidi Vandebosch), Netherlands (Rutger Leukfeldt) and Austria (Takuya Yanagida and Christiane Spiel).

Most-cited publications

The most-cited literature items are displayed in Table 5 . The article which recorded the highest number of citations was ‘Psychological, Physical, and Academic Correlates of Cyberbullying and Traditional Bullying’ (442 citations) by Robin M. Kowalski et al. published in Journal of Adolescent Health , 2013. Seven of ten most-cited articles were about cyberbullying; focused on youth population; made comparisons between cyberbullying and traditional bullying; analyzed the impact of several factors such as psychological, physical, academic factors or use of Internet; discussed on preventing strategies. The other publications studied victimization of cyberstalking and cyber dating abuse. All most-cited articles were from 2015 and earlier.

Of the top productive authors, only Bradford W. Reyns had an article appeared in the group of most-cited publications. His article ‘Being Pursued Online: Applying Cyberlifestyle-Routine Activities Theory to Cyberstalking Victimization’ (2011) was cited 172 times.

• Co-authorship analysis

“Scientific collaboration is a complex social phenomenon in research” (Glänzel and Schubert 2006 , p. 257) and becomes the increasing trend in individual, institutional and national levels. In bibliometric analysis, it is common to assess the productivity and international collaboration of research; identify key leading researchers, institutions, or countries (E Fonseca et al. 2016 ) as well as potential collaborators in a specific scientific area (Romero and Portillo-Salido 2019 ) by co-authorship analysis which constructs networks of authors and countries (Eck and Waltman 2020 ).

This section analyses international collaboration relevant to research of cybercrime victimization among authors, institutions, and countries during 2010–2020 through visualization of VOS Viewer software.

Collaboration between authors

Referring to the threshold of choose in this analysis, minimum number of documents of author is three and there were 80 authors for final results. Figure  4 illustrates the relationships between 80 scientists who study in subject of cybercrime victimization during 2010–2020. It shows several big groups of researchers (Wright’s group, Vandebosch’s group, or Holt’s group), while numerous authors had limited or no connections to others (Sheri Bauman, Michelle K. Demaray or Jennifer D. Shapka).

Collaboration among authors via network visualization (threshold three articles for an author, displayed 80 authors)

Figure  5 displayed a significant network containing 23 authors who were active in collaboration in detail. The displayed items in Fig.  5 are divided into five clusters coded with distinctive colors, including red, green, blue, yellow, and purple. Each author item was represented by their label and a circle; the size of label and circle are depended on the weight of the item, measured by the total publications (Eck and Waltman 2020 ). The thickness of lines depends on the strength of collaboration (Eck and Waltman 2020 ).

Collaboration among authors via network visualization (threshold three articles for an author, displayed 23 authors)

The most significant cluster was red one which is comprised of six researchers: Michelle F. Wright, Sebastian Wachs, Yan Li, Anke Gorzig, Manuel Gamez-Guadix and Esther Calvete. The remarked author for the red cluster was Michelle F. Wright whose value of total link strength is 24. She had the strongest links with Sebastian Wachs; closely link with Yan Li, Anke Gorzig, Manuel Gamez-Guadix and collaborated with authors of yellow cluster, including Shanmukh V. Kamble, Li Lei, Hana Machackova, Shruti Soudi as well as Takuya Yanagida of blue cluster. Michelle F. Wright who obtained the largest number of published articles based on criteria of this study made various connections with other scholars who were from many different institutions in the world. This is also an effective way to achieve more publications.

Takuya Yanagida was the biggest node for the blue cluster including Petra Gradinger, Daniel Graf, Christiane Spiel, Dagmar Strohmeier. Total link strength for Takuya Yanagida was 28; twelve connections. It is observed that Takuya Yanagida’ s research collaboration is definitely active. Besides, other research groups showed limited collaborations comparing with the red and blue ones.

Collaboration between institutions

The connections among 156 institutions which published at least two documents per one are shown in Fig.  6 . Interestingly, there is obvious connections among several distinctive clusters which were coded in color of light steel blue, orange, purple, steel blue, green, red, yellow, light red, dark turquoise, light blue, brown and light green. These clusters created a big chain of connected institutions and were in the center of the figure, while other smaller clusters or unlinked bubbles (gray color) were distributed in two sides. The biggest chain consisted of most of productive institutions such as Masaryk University, Michigan State University, University of Antwerp, Weber State University, University of Cordoba, Edith Cowan University, University of Cincinnati, University of Victoria, University of Vienna, and University of Seville.

Collaboration among institutions via network visualization (threshold two articles for an institution, 156 institutions were displayed)

Light steel blue and orange clusters presented connections among organizations from Australia. Light green included institutions from Netherland, while turquoise and light blue consisted of institutions from the USA. Yellow cluster was remarked by the various collaborations among institutions from China and Hong Kong Special Administrative Region (Renmin University of China and South China Normal University, University of Hong Kong, the Hong Kong Polytechnic University and the Chinese University of Hong Kong), the USA (University of Virginia), Cyprus (Eastern Mediterranean University), Japan (Shizuoka University), India (Karnataka University) and Austria (University Applied Sciences Upper Austria). Central China Normal University is another Chinese institution which appeared in Fig.  5 , linking with Ministry of Education of the People’s Republic of China, Suny Stony Brook and University of Memphis from the USA.

Masaryk University and Michigan State University demonstrated their productivity in both the quantity of publications and the collaboration network. They were active in research collaboration, reaching twelve and eleven links, respectively, with different institutions, but focused much on networking with institutions in the USA and Europe.

Collaboration between countries

The collaboration among 45 countries which published at least one SSCI documents of cybercrime victimization during the given period was examined in VOS Viewer but just 42 items were displayed via overlay visualization. Figure  7 depicts the international collaborations among significant countries. The USA is the biggest bubble due to its biggest number of documents and shows connections with 26 countries/regions in Euro, Asia, Australia, Middle East. Excepting European countries, England collaborate with the USA, Australia, South Korea, Japan, Thailand, Singapore, Sri Lanka, and Colombia. Spain and Germany almost focus on research network within Euro. China has the strongest tie with the USA, link with Australia, Germany, Czech Republic, Austria, Cyprus and Turkey, Japan, Indian, Vietnam.

Collaboration among countries via overlay visualization

Color bar in Fig.  7 is determined by the average publication year of each country and the color of circles based on it. It is unsurprised that the USA, Australia, England, or Spain shows much research experience in this field and maintain the large number of publications steadily. Interestingly, although the average publication year of South Korea or Cyprus was earlier than other countries (purple color), their quantities of documents were moderate. The new nodes (yellow circles) in the map included Vietnam, Norway, Pakistan, Ireland, Scotland, Switzerland.

Keywords and co-occurrence

The present paper examined the related themes and contents in research of cybercrime victimization during 2010–2020 through collecting author keywords, adding several keywords from tiles and abstracts. Besides, this study also conducted co-occurrence analysis of author keywords to show the relationships among these keywords.

The keywords were collected and categorized into 15 themes in Table 6 , including cybercrime; sample and demographic factors; location; theory; methodology; technology, platform, and related others; psychology and mental health; physical health; family; school; society; crimes and other deviant behaviors; victim; prevention and intervention; and others.

In the theme of cybercrime, there were numerous types of cybercrimes such as cyberbullying, cyber aggression, cyberstalking, cyber harassment, sextortion and other cyber dating crimes, cyber fraud, identity theft, phishing, hacking, malware, or ransomware. Generally, the frequency of interpersonal cybercrimes or cyber-enable crimes was much higher than cyber-dependent crimes. Cyberbullying was the most common cybercrime in research.

Relating to sample and demographic factors, there were sample of children, adolescent, adults, and the elder who were divided into more detail levels in each research; however, adolescent was the most significant sample. Besides, demographic factor of gender received a remarked concern from scholars.

It is usual that most of the research were carried out in one country, in popular it was the USA, Spain, Germany, England, Australia, Canada or Netherland but sometimes the new ones were published such as Chile, Vietnam, Thailand or Singapore. It was witnessed that some studies showed data collected from a group of countries such as two countries (Canada and the United State), three countries (Israel, Litva, Luxembourg), four countries (the USA, the UK, Germany, and Finland), or six Europe countries (Spain, Germany, Italy, Poland, the United Kingdom and Greece).

A wide range of theories were applied in this research focusing on criminological and psychological theories such as Routine Activities Theory, Lifestyle—Routine Activities Theory, General Strain Theory, the Theory of Reasoned Action or Self-control Theory.

Table 6 indicated a lot of different research methods covering various perspective of cybercrime victimization: systematic review, questionnaire survey, interview, experiment, mix method, longitudinal study, or cross-national research; many kinds of analysis such as meta-analysis, social network analysis, latent class analysis, confirmatory factor analysis; and a wide range of measurement scales which were appropriate for each variable.

Topic of cybercrime victimization had connections with some main aspects of technology (information and communication technologies, internet, social media or technology related activities), psychology (self-esteem, fear, attitude, personality, psychological problems, empathy, perceptions or emotion), physical health, family (parents), school (peers, school climate), society (norms, culture, social bonds), victim, other crimes (violence, substance use), prevention and intervention.

Co-occurrence analysis was performed with keywords suggested by authors and the minimum number of occurrences per word is seven. The result showed 36 frequent keywords which clustered into five clusters as illustrated in Fig.  8 .

Co-occurrence between author keywords via network visualization (the minimum number of occurrences per word is seven, 36 keywords were displayed)

Figure  8 illustrates some main issues which were concerned in subject of cybercrime victimization, as well as the relationship among them. Fifteen most frequent keywords were presented by big bubbles, including: ‘cyberbullying’ (174 times), ‘cyber victimization’ (90 times), ‘adolescent’ (79 times), ‘bullying’ (66 times), ‘victimization’ (56 times), ‘cybercrime’ (40 times), ‘cyber aggression’ (37 times), ‘depression’ (23 times), ‘aggression’ (14 times), ‘routine activities theory’ (13 times), ‘cyberstalking’ (11 times), ‘gender’ (11 times), ‘longitudinal’ (10 times), ‘peer victimization’ (10 times) and ‘self-esteem’ (10 times).

‘Cyberbullying’ linked with many other keywords, demonstrating the various perspectives in research of this topic. The thick lines which linked ‘cyberbullying’ and ‘bullying’, ‘adolescent’, ‘cyber victimization’, ‘victimization’ showed the strong connections between them; there were close relationship between ‘cyber aggression’, ‘bystander”, ‘self-esteem’ or ‘moral disengagement’ and ‘cyberbullying’.

‘Cybercrime’ had strong links with ‘victimization’, ‘routine activities theory’. In Fig.  8 , the types of cybercrime which occurred at least seven times were: cyberbullying, cyber aggression, hacking, cyberstalking, and cyber dating abuse.

The increasing trend over the years reveals the increasing concern of scholarly community on this field, especially in the boom of information technology and other communication devices and the upward trend in research of cyberspace-related issues (Altarturi et al. 2020 ; Leung et al. 2017 ; Serafin et al. 2019 ). It predicts the growth of cybercrime victimization research in future.

Psychology was the more popular research areas in database, defeating criminology penology. As part of the ‘human factors of cybercrime’, human decision-making based on their psychological perspectives plays as a hot topic in cyber criminology (Leukfeldt and Holt 2020 ). Then, it is observed that journals in psychology field was more prevalent in top of productive sources. Besides, journal Computers in Human Behavior ranked first in total publications, but Journal of Youth and Adolescence ranked higher place in the average citations per document. Generally, top ten journals having highest number of publications on cybercrime victimization are highly qualified ones and at least 10 years in publishing industry.

The USA demonstrated its leading position in the studied domain in terms of total publications as well as the various collaborations with other countries. The publications of the USA occupied much higher than the second and third countries: England and Spain. It is not difficult to explain for this fact due to the impressive productivity of institutions and authors from the USA. A third of top twelve productive institutions were from the USA. Three leading positions of top ten productive authors based on document count were from institutions of the USA, number one was Michelle F. Wright; others were Thomas J. Holt and Bradford W. Reyns.

Furthermore, these authors also participated in significant research groups and become the important nodes in those clusters. The most noticeable authors in co-authors network were Michelle F. Wright. The US institutions also had strong links in research network. The USA was likely to be open in collaboration with numerous countries from different continents in the world. It was assessed to be a crucial partner for others in the international co-publication network (Glänzel and Schubert 2006 ).

As opposed to the USA, most of European countries prefer developing research network within Europe and had a limited collaboration with other areas. Australia, the USA, or Japan was in a small group of countries which had connections with European ones. Nevertheless, European countries still showed great contributions for research of cybercrime victimization and remained stable links in international collaboration. The prominent authors from Euro are Rosario Ortega-Ruiz, Constantinos M. Kokkinos or Rutger Leukfeldt.

It is obvious that the limited number of publications from Asia, Middle East, Africa, or other areas resulted in the uncomprehensive picture of studied subject. For example, in the Southeast Asia, Malaysia and Vietnam lacked the leading authors with their empirical studies to review and examine the nature of cybercrimes, though they are facing to practical challenges and potential threats in the cyberspace (Lusthaus 2020a , b ). The present study indicated that Vietnam, Ireland, or Norway was the new nodes and links in research network.

Several nations which had a small number of publications such as Vietnam, Thailand, Sri Lanka, or Chile started their journey of international publications. It is undeniable that globalization and the context of global village (McLuhan 1992 ) requires more understanding about the whole nations and areas. Conversely, each country or area also desires to engage in international publications. Therefore, new nodes and clusters are expected to increase and expand.

The findings indicated that cyberbullying was the most popular topic on research of cybercrime victimization over the given period. Over a half of most-cited publications was focus on cyberbullying. Additionally, ‘cyberbullying’ was the most frequent author keyword which co-occurred widely with distinctive keywords such as ‘victimization’, ‘adolescents’, ‘bullying’, ‘social media’, ‘internet’, ‘peer victimization’ or ‘anxiety’.

By reviewing keywords, several research gaps were indicated. Research samples were lack of population of the children and elders, while adolescent and youth were frequent samples of numerous studies. Although young people are most active in cyberspace, it is still necessary to understand other populations. Meanwhile, the elderly was assumed to use information and communication technologies to improve their quality of life (Tsai et al. 2015 ), their vulnerability to the risk of cybercrime victimization did not reduce. Those older women were most vulnerable to phishing attacks (Lin et al. 2019 ; Oliveira et al. 2017 ). Similarly, the population of children with distinctive attributes has become a suitable target for cybercriminals, particularly given the context of increasing online learning due to Covid-19 pandemic impacts. These practical gaps should be prioritized to focus on research for looking the suitable solutions in the future. Besides, a vast majority of research were conducted in the scope of one country; some studies collected cross-national data, but the number of these studies were moderate and focused much on developed countries. There are rooms for studies to cover several countries in Southeast Asia or South Africa.

Furthermore, although victims may be both individuals and organizations, most of research concentrated much more on individuals rather than organizations or companies. Wagen and Pieters ( 2020 ) indicated that victims include both human and non-human. They conducted research covering cases of ransomware victimization, Bonet victimization and high-tech virtual theft victimization and applying Actor-Network Theory to provide new aspect which did not aim to individual victims. The number of this kind of research, however, was very limited. Additionally, excepting cyberbullying and cyber aggression were occupied the outstanding quantity of research, other types of cybercrime, especially, e-whoring, or social media-related cybercrime should still be studied more in the future.

Another interesting topic is the impact of family on cybercrime victimization. By reviewing keyword, it is clear that the previous studies aimed to sample of adolescent, hence, there are many keywords linking with parents such as ‘parent-adolescent communication’, ‘parent-adolescent information sharing’, ‘parental mediation’, ‘parental monitoring of cyber behavior’, ‘parental style’. As mentioned above, it is necessary to research more on sample of the elder, then, it is also essential to find out how family members affect the elder’s cybercrime victimization.

It is a big challenge to deal with problems of cybercrime victimization because cybercrime forms become different daily (Näsi et al. 2015 ). Numerous researchers engage in understanding this phenomenon from various angles. The current bibliometric study assessed the scholarly status on cybercrime victimization during 2010–2020 by retrieving SSCI articles from WoS database. There is no study that applied bibliometric method to research on the examined subject. Hence, this paper firstly contributed statistical evidence and visualized findings to literature of cybercrime victimization.

Statistical description was applied to measure the productive authors, institutions, countries/regions, sources, and most-cited documents, mainly based on publication and citation count. The international collaborations among authors, institutions, and countries were assessed by co-authors, while the network of author keywords was created by co-occurrence analysis. The overall scholarly status of cybercrime victimization research was drawn clearly and objectively. The research trend, popular issues and current gaps were reviewed, providing numerous suggestions for policymakers, scholars, and practitioners about cyber-related victimization (Pickering and Byrne 2014 ). Accordingly, the paper indicated the most prevalent authors, most-cited papers but also made summary of contributions of previous research as well as identified research gaps. First, this article supports for PhD candidates or early-career researchers concerning about cybercrime victimization. Identifying the leading authors, remarked journals, or influencing articles, gaps related to a specific research topic is important and useful task for new researchers to start their academic journey. Although this information is relatively simple, it takes time and is not easy for newcomers to find out, especially for ones in poor or developing areas which have limited conditions and opportunities to access international academic sources. Thus, the findings in the current paper provided for them basic but necessary answers to conduct the first step in research. Secondly, by indicating research gaps in relevance to sample, narrow topics or scope of country, the paper suggests future study fulfilling them to complete the field of cybercrime victimization, especial calling for publications from countries which has had a modest position in global research map. Science requires the balance and diversity, not just focusing on a few developed countries or areas. Finally, the present study assists researchers and institutions to determined strategy and potential partners for their development of research collaborations. It not only improve productivity of publication but also create an open and dynamic environment for the development of academic field.

Despite mentioned contributions, this study still has unavoidable limitations. The present paper just focused on SSCI articles from WoS database during 2010–2020. It did not cover other sources of databases that are known such as Scopus, ScienceDirect, or Springer; other types of documents; the whole time; or articles in other languages excepting English. Hence it may not cover all data of examined subject in fact. Moreover, this bibliometric study just performed co-authorship and co-occurrence analysis. The rest of analysis such as citation, co-citation and bibliographic coupling have not been conducted. Research in the future is recommended to perform these kinds of assessment to fill this gap. To visualize the collaboration among authors, institutions, countries, or network of keywords, this study used VOS Viewer software and saved the screenshots as illustrations. Therefore, not all items were displayed in the screenshot figures.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Ho, H.T.N., Luong, H.T. Research trends in cybercrime victimization during 2010–2020: a bibliometric analysis. SN Soc Sci 2 , 4 (2022). https://doi.org/10.1007/s43545-021-00305-4

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Received : 13 September 2021

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Published : 06 January 2022

DOI : https://doi.org/10.1007/s43545-021-00305-4

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