Grad Coach

Research Topics & Ideas: Data Science

50 Topic Ideas To Kickstart Your Research Project

Research topics and ideas about data science and big data analytics

If you’re just starting out exploring data science-related topics for your dissertation, thesis or research project, you’ve come to the right place. In this post, we’ll help kickstart your research by providing a hearty list of data science and analytics-related research ideas , including examples from recent studies.

PS – This is just the start…

We know it’s exciting to run through a list of research topics, but please keep in mind that this list is just a starting point . These topic ideas provided here are intentionally broad and generic , so keep in mind that you will need to develop them further. Nevertheless, they should inspire some ideas for your project.

To develop a suitable research topic, you’ll need to identify a clear and convincing research gap , and a viable plan to fill that gap. If this sounds foreign to you, check out our free research topic webinar that explores how to find and refine a high-quality research topic, from scratch. Alternatively, consider our 1-on-1 coaching service .

Research topic idea mega list

Data Science-Related Research Topics

  • Developing machine learning models for real-time fraud detection in online transactions.
  • The use of big data analytics in predicting and managing urban traffic flow.
  • Investigating the effectiveness of data mining techniques in identifying early signs of mental health issues from social media usage.
  • The application of predictive analytics in personalizing cancer treatment plans.
  • Analyzing consumer behavior through big data to enhance retail marketing strategies.
  • The role of data science in optimizing renewable energy generation from wind farms.
  • Developing natural language processing algorithms for real-time news aggregation and summarization.
  • The application of big data in monitoring and predicting epidemic outbreaks.
  • Investigating the use of machine learning in automating credit scoring for microfinance.
  • The role of data analytics in improving patient care in telemedicine.
  • Developing AI-driven models for predictive maintenance in the manufacturing industry.
  • The use of big data analytics in enhancing cybersecurity threat intelligence.
  • Investigating the impact of sentiment analysis on brand reputation management.
  • The application of data science in optimizing logistics and supply chain operations.
  • Developing deep learning techniques for image recognition in medical diagnostics.
  • The role of big data in analyzing climate change impacts on agricultural productivity.
  • Investigating the use of data analytics in optimizing energy consumption in smart buildings.
  • The application of machine learning in detecting plagiarism in academic works.
  • Analyzing social media data for trends in political opinion and electoral predictions.
  • The role of big data in enhancing sports performance analytics.
  • Developing data-driven strategies for effective water resource management.
  • The use of big data in improving customer experience in the banking sector.
  • Investigating the application of data science in fraud detection in insurance claims.
  • The role of predictive analytics in financial market risk assessment.
  • Developing AI models for early detection of network vulnerabilities.

Research topic evaluator

Data Science Research Ideas (Continued)

  • The application of big data in public transportation systems for route optimization.
  • Investigating the impact of big data analytics on e-commerce recommendation systems.
  • The use of data mining techniques in understanding consumer preferences in the entertainment industry.
  • Developing predictive models for real estate pricing and market trends.
  • The role of big data in tracking and managing environmental pollution.
  • Investigating the use of data analytics in improving airline operational efficiency.
  • The application of machine learning in optimizing pharmaceutical drug discovery.
  • Analyzing online customer reviews to inform product development in the tech industry.
  • The role of data science in crime prediction and prevention strategies.
  • Developing models for analyzing financial time series data for investment strategies.
  • The use of big data in assessing the impact of educational policies on student performance.
  • Investigating the effectiveness of data visualization techniques in business reporting.
  • The application of data analytics in human resource management and talent acquisition.
  • Developing algorithms for anomaly detection in network traffic data.
  • The role of machine learning in enhancing personalized online learning experiences.
  • Investigating the use of big data in urban planning and smart city development.
  • The application of predictive analytics in weather forecasting and disaster management.
  • Analyzing consumer data to drive innovations in the automotive industry.
  • The role of data science in optimizing content delivery networks for streaming services.
  • Developing machine learning models for automated text classification in legal documents.
  • The use of big data in tracking global supply chain disruptions.
  • Investigating the application of data analytics in personalized nutrition and fitness.
  • The role of big data in enhancing the accuracy of geological surveying for natural resource exploration.
  • Developing predictive models for customer churn in the telecommunications industry.
  • The application of data science in optimizing advertisement placement and reach.

Recent Data Science-Related Studies

While the ideas we’ve presented above are a decent starting point for finding a research topic, they are fairly generic and non-specific. So, it helps to look at actual studies in the data science and analytics space to see how this all comes together in practice.

Below, we’ve included a selection of recent studies to help refine your thinking. These are actual studies,  so they can provide some useful insight as to what a research topic looks like in practice.

  • Data Science in Healthcare: COVID-19 and Beyond (Hulsen, 2022)
  • Auto-ML Web-application for Automated Machine Learning Algorithm Training and evaluation (Mukherjee & Rao, 2022)
  • Survey on Statistics and ML in Data Science and Effect in Businesses (Reddy et al., 2022)
  • Visualization in Data Science VDS @ KDD 2022 (Plant et al., 2022)
  • An Essay on How Data Science Can Strengthen Business (Santos, 2023)
  • A Deep study of Data science related problems, application and machine learning algorithms utilized in Data science (Ranjani et al., 2022)
  • You Teach WHAT in Your Data Science Course?!? (Posner & Kerby-Helm, 2022)
  • Statistical Analysis for the Traffic Police Activity: Nashville, Tennessee, USA (Tufail & Gul, 2022)
  • Data Management and Visual Information Processing in Financial Organization using Machine Learning (Balamurugan et al., 2022)
  • A Proposal of an Interactive Web Application Tool QuickViz: To Automate Exploratory Data Analysis (Pitroda, 2022)
  • Applications of Data Science in Respective Engineering Domains (Rasool & Chaudhary, 2022)
  • Jupyter Notebooks for Introducing Data Science to Novice Users (Fruchart et al., 2022)
  • Towards a Systematic Review of Data Science Programs: Themes, Courses, and Ethics (Nellore & Zimmer, 2022)
  • Application of data science and bioinformatics in healthcare technologies (Veeranki & Varshney, 2022)
  • TAPS Responsibility Matrix: A tool for responsible data science by design (Urovi et al., 2023)
  • Data Detectives: A Data Science Program for Middle Grade Learners (Thompson & Irgens, 2022)
  • MACHINE LEARNING FOR NON-MAJORS: A WHITE BOX APPROACH (Mike & Hazzan, 2022)
  • COMPONENTS OF DATA SCIENCE AND ITS APPLICATIONS (Paul et al., 2022)
  • Analysis on the Application of Data Science in Business Analytics (Wang, 2022)

As you can see, these research topics are a lot more focused than the generic topic ideas we presented earlier. So, for you to develop a high-quality research topic, you’ll need to get specific and laser-focused on a specific context with specific variables of interest.  In the video below, we explore some other important things you’ll need to consider when crafting your research topic.

Get 1-On-1 Help

If you’re still unsure about how to find a quality research topic, check out our Research Topic Kickstarter service, which is the perfect starting point for developing a unique, well-justified research topic.

Research Topic Kickstarter - Need Help Finding A Research Topic?

You Might Also Like:

IT & Computer Science Research Topics

Submit a Comment Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

  • Print Friendly

Emerging trends and new developments in information science: a document co-citation analysis (2009–2016)

  • Published: 07 March 2018
  • Volume 115 , pages 869–892, ( 2018 )

Cite this article

research topics on information science

  • Jianhua Hou 1 ,
  • Xiucai Yang 2 &
  • Chaomei Chen 3  

8979 Accesses

213 Citations

3 Altmetric

Explore all metrics

Characterizing the structure of knowledge, the evolution of research topics, and the emergence of topics has always been an important part of information science (IS). Our previous scientometric review of IS provided a snapshot of this fast-growing field up to the end of 2008. This new study aims to identify emerging trends and new developments appearing in the subsequent 7574 articles published in 10 IS journals between 2009 and 2016, including 20,960 references. The results of a document co-citation analysis show great changes in the research topics in the IS domain. The positions of certain core topics found in the previous study, namely, information retrieval, webometrics, and citation behavior, have been replaced by scientometric indicators (H-index), citation analysis (citation performance and bibliometrics), scientific collaboration, and information behavior in the most recent period of 2009–2016. Dual-map overlays of journals show that the knowledge base of IS research has shifted considerably since 2010, with emerging topics including scientific evaluation indicators, altmetrics, science mapping and visualization, bibliometrics, citation analysis, and scientific collaboration.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save.

  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

research topics on information science

Evolution of research subjects in library and information science based on keyword, bibliographical coupling, and co-citation analyses

Some bibliometric procedures for analyzing and evaluating research fields.

research topics on information science

iMetrics: the development of the discipline with many names

Aharony, N. (2012). Library and information science research areas: A content analysis of articles from the top 10 journals 2007–8. Journal of Librarianship and Information Science, 44 (1), 27–35.

Article   Google Scholar  

Albarran, P., & Ruiz-Castillo, J. (2011). References made and citations received by scientific articles. Journal of the American Society for Information Science and Technology, 62 (1), 40–49.

Astrom, F. (2007). Changes in the LIS research front: Time-sliced co-citation analyses of LIS journal articles, 1990–2004. Journal of the American Society for Information Science and Technology, 58 (7), 947–957.

Bar-Ilan, J. (2008). Informetrics at the beginning of the 21st century—A review. Journal of Informetrics, 2 (1), 1–52.

Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008 (10), P10008.

Bornmann, L. (2012). Measuring the societal impact of research. EMBO Reports, 13 (8), 673–676.

Bornmann, L. (2013). How to analyze percentile citation impact data meaningfully in bibliometrics: The statistical analysis of distributions, percentile rank classes, and top-cited papers. Journal of the American Society for Information Science and Technology, 64 (3), 587–595.

Bornmann, L., & Daniel, H. D. (2008). What do citation counts measure? A review of studies on citingbehavior. Journal of Documentation, 64 (1), 45–80.

Bornmann, L., Mutz, R., Hug, S. E., & Daniel, H. D. (2011). A multilevel meta-analysis of studies reporting correlations between the h index and 37 different h index variants. Journal of Informetrics, 5 (3), 346–359.

Chang, Y. W., Huang, M. H., & Lin, C. W. (2015). Evolution of research subjects in library and information science based on keyword, bibliographical coupling, and co-citation analyses. Scientometrics, 105 (3), 2071–2087.

Chen, C. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology, 57 (3), 359–377.

Chen, C. (2017). Science mapping: A systematic review of the literature. Journal of Data and Information Science, 2 (2), 1–39.

Chen, C., Dubin, R., & Kim, M. C. (2014). Emerging trends and new developments inregenerativemedicine: A scientometric update (2000–2014). Expert Opinion on Biological Therapy, 14 (9), 1295–1317.

Chen, C., Hu, Z., Liu, S., & Tseng, H. (2012). Emerging trends in regenerative medicine: A scientometric analysis in CiteSpace. Expert Opinions on Biological Therapy, 12 (5), 593–608.

Chen, C., Ibekwe-SanJuan, F., & Hou, J. H. (2010). The structure and dynamics of cocitation clusters: A multiple-perspective co-citation analysis. Journal of the American Society for Information Science and Technology, 61 (7), 1386–1409.

Chen, C., & Leydesdorff, L. (2014). Patterns of connections and movements in dual-map overlays: A new method of publication portfolio analysis. Journal of the American Society for Information Science and Technology, 65 (2), 334–351.

Google Scholar  

Cimenler, O., Reeves, K. A., & Skvoretz, J. (2014). A regression analysis of researchers’ social network metrics on their citation performance in a college of engineering. Journal of Informetrics, 8 (3), 667–682.

D'Angelo, C. A., Giuffrida, C., & Abramo, G. (2011). A heuristic approach to author name disambiguation in bibliometrics databases for large-scale research assessments. Journal of the American Society for Information Science and Technology, 62 (2), 257–269.

De Bellis, N. (2009). Bibliometrics and citation analysis: From the science citation index to cybermetrics . Lanham, MD: Scarecrow Press.

Egghe, L. (2006). Theory and practice of the g-index. Scientometrics, 69 (1), 131–152.

Article   MathSciNet   Google Scholar  

Engels, T. C. E., Ossenblok, T. L. B., & Spruyt, E. H. J. (2012). Changing publication patterns in the Social Sciences and Humanities, 2000–2009. Scientometrics, 93 (2), 373–390.

Eysenbach, G. (2011). Can tweets predict citations? Metrics of social impact based on twitter and correlation with traditional metrics of scientific impact. Journal of Medical Internet Research, 13 (4), e123.

Fiala, D., Subelj, L., Zitnikl, S., & Bajec, M. (2015). Do PageRank-based author rankings outperform simple citation counts? Journal of Informetrics, 9 (2), 334–348.

Fidel, R. (2012). An Ecological Approach to Information Behavior: Conclusions (pp. 253–254). Cambridge: MIT Press.

Book   Google Scholar  

Finardi, U. (2013). Correlation between journal impact factor and citation performance: An experimental study. Journal of Informetrics, 7 (2), 357–370.

Franceschet, M. (2010). A comparison of bibliometric indicators for computer science scholars and journals on Web of Science and Google Scholar. Scientometrics, 83 (1), 243–258.

Glanzel, W., & Schubert, A. (2005). Domesticity and internationality in co-authorship, references and citations. Scientometrics, 65 (3), 323–342.

Glenisson, P., Glänzel, W., & Persson, O. (2005a). Combining full text analysis and bibliometric indicators. A pilot study. Scientometrics, 63 (1), 163–180.

Glenisson, P., Jassens, F., & Moor, D. B. (2005b). Combining full text and bibliometric information in mapping scientific disciplines. Information Processing and Management, 41 (6), 1548–1572.

González-Pereira, B., Guerrero-Bote, V. P., & Moya-Anegón, F. (2010). A new approach to the metric of journals’ scientific prestige: The SJR indicator. Journal of Informetrics, 4 (3), 379–391.

Gorraiz, J., Purnell, P. J., & Glanzel, W. (2013). Opportunities for and limitations of the book citation index. Journal of the American Society for Information Science and Technology, 64 (7), 1388–1398.

Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output that takes into account the effect of multiple coauthorship. Scientometrics, 85 (3), 741–754.

Ibekwe-SanJuan, F. (2009). Information science in the web era: A term-based approach to domain mapping. In Annual meeting of american society for information science and technology , November 6–11, 2009, Vancouver, Canada (pp 1–13).

Janssens, F., Glänzel, W., & Moor, D. B. (2008). A hybrid mapping of information science. Scientometrics, 75 (3), 607–631.

Janssens, F., Leta, J., Glänzel, W., & de Moor, B. (2006). Towards mapping library and information science. Information Processing and Management, 42 (6), 1614–1642.

Jassens, F., Glenisson, P., Glänzel, W., & De Moor, B. (2005). Co-clustering approaches to integrate lexical and bibliographical information. ISSI 2005. In Proceedings of the 10th international conference of the international society for scientometrics and informetrics, Vols. 1 and 2(pp. 284–289).

Jeong, Y. K., Song, M., & Ding, Y. (2014). Content-based author co-citation analysis. Journal of Informetrics, 8 (1), 197–211.

Jin, B. H., Liang, L. M., Rousseau, R., & Egghe, L. (2007). The R- and AR-indices: Complementing the h-index. Chinese Science Bulletin, 52 (6), 855–863.

Kim, M. C., & Chen, C. (2015). A scientometric review of emerging trends and new developments in recommendation systems. Scientometrics, 104 (1), 239–263.

Klavans, R., & Boyack, K. W. (2011). Using global mapping to create more accurate document-level maps of research fields. Journal of the American Society for Information Science and Technology, 62 (1), 1–18.

Klavans, R., Persson, O., & Boyack, K. W. (2009). Coco at the copacabana: Introducing co-cited author pair co-citation (Coco) analysis. In Proceedings of the international conference on scientometrics and informetrics . Rio de JaneiroBRAZIL, 2009.

Li, X. F., Jiang, W. M., Yang, H. L., Tang, T. S., Gong, X. H., Yuan, J., et al. (2010). Surgical treatment of chronic C1-C2 dislocation with absence of odontoid process using C1 hooks with C2 pedicle screws a case report and review of literature. SPINE, 36 (18), E1245–E1249.

Liu, X. M., Zhou, X. Q., & Lu, C. (2005). Four-wave mixing assisted stability enhancement: Theory, experiment, and application. Optics Letters, 30 (17), 2257–2259.

Liu, Y., & Yang, Y. L. (2014). Empirical study of L-sequence: The basic h-index sequence for cumulative publications with consideration of the yearly citation performance. Journal of Informetrics, 8 (3), 478–485.

Milojević, S., & Leydesdorff, L. (2013). Information metrics (iMetrics): A research specialty with a socio-cognitive identity? Scientometrics, 95 (1), 141–157.

Milojević, S., Sugimoto, C. R., Yan, E., & Ding, Y. (2011). The cognitive structure of library and information science: Analysis of article title words. Journal of the American Society for Information Science and Technology, 62 (10), 1933–1953.

Nederhof, A. J. (2006). Bibliometric monitoring of research performance in the social sciences and the humanities: A review. Scientometrics, 66 (1), 81–100.

Nisonger, T. E., & Davis, C. H. (2005). The perception of library and information science journals by LIS education deans and ARL library directors: A replication of the Kohl-Davis study. College and Research Libraries, 66 (4), 341–377.

Persson, O. (1994). The intellectual base and research fronts of JASIS 1986–1990. Journal of the American Society for Information Science, 45 (1), 31–38.

Persson, O. (2001). All author citations versus first author citations. Scientometrics, 50 (2), 339–344.

Persson, O. (2010). Identifying research themes with weighted direct citation links. Journal of Informetrics, 4 (3), 415–422.

Priem, J., & Hemminger, B. H. (2010). Scientometrics 2.0: New metrics of scholarly impact on the social Web. First Monday . https://doi.org/10.5210/fm.v15i7.2874 .

Rafols, I., & Meyer, M. (2010). Diversity and network coherence as indicators of interdisciplinarity: Case studies in bionanoscience. Scientometrics, 82 (2), 263–287.

Rafols, I., Porter, A. L., & Leydesdorff, L. (2010). Science overlay maps: A new tool for research policy and library management. Journal of the American Society for Information Science and Technology, 61 (9), 1871–1887.

Sonnenwald, D. H. (2007). Scientific collaboration. Annual Review of Information Science and Technology, 41 , 643–681.

Stirling, A., Lobstein, T., & Millstone, E. (2007). Methodology for obtaining stakeholder assessments of obesity policy options in the PorGrow project. Obesity Reviews, 8 (z2), 17–27.

Thelwall, M. (2016). Citation count distributions for large monodisciplinary journals. Journal of Informetrics, 10 (3), 863–874.

Thelwall, M., Haustein, S., Lariviere, V., & Sugimoto, C. R. (2013). Do altmetrics work? Twitter and ten other social web services. Plos One, 8 (5), e64841.

Thelwall, M., & Maflahi, N. (2015). How important is computing technology for library and information science research? Library and Information Science Research, 37 (1), 40–50.

Tuomaala, O., Jarvelin, K., & Vakkari, P. (2014). Evolution of library and information science, 1965–2005: Content analysis of journal articles. Journal of the Association for Information Science and Technology., 65 (7), 1446–1462.

VanDenBesselaar, P., & Heimeriks, G. (2006). Mapping research topics using word-reference co-occurrences: A method and an exploratory case study. Scientometrics, 68 (3), 377–393.

van Eck, N. J., & Waltman, L. (2009). How to normalize cooccurrence data? An analysis of some well-known similarity measures. Journal of the American Society for Information Science and Technology, 60 (8), 1635–1651.

van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84 (2), 523–538.

Wagner, C. S., Shehata, S., Henzler, K., Yuan, J. Y., & Wittemann, A. (2011). Towards nanoscale composite particles of dual complexity. Journal of Colloid and Interface Science, 355 (1), 115–123.

Waltman, L., Calero-Medina, C., Kosten, J., Noyons, E. C. M., Tijssen, R. J. W., van Eck, N. J., et al. (2012). The Leiden ranking 2011/2012: Data collection, indicators, and interpretation. Journal of the American Society for Information Science and Technology, 63 (12), 2419–2432.

Waltman, L., & Van Eck, N. J. (2012a). A new methodology for constructing a publication-level classification system of science. Journal of the American Society for Information Science and Technology, 63 (12), 2378–2392.

Waltman, L., & Van Eck, N. J. (2012b). The inconsistency of the h-index. Journal of the American Society for Information Science and Technology, 63 (2), 406–415.

Wang, J., Duncan, D., Shi, Z., & Zhang, B. (2013). WEB–based GEne SeT AnaLysis Toolkit (WebGestalt): Update 2013. Nucleic Acids Research, 41 (W1), W77–W83.

Weingart, P. (2005). Impact of bibliometrics upon the science system:Inadvertent consequences? Scientometrics, 62 (1), 117–131.

White, H. D. (2003). Pathfinder networks and author cocitation analysis: A remapping of paradigmatic information scientists. Journal of the American Society for Information Science and Technology, 54 (5), 423–434.

White, H. D., & Griffith, B. C. (1981). Author cocitation: A literature measure of intellectual structure. Journal of the American Society for Information Science, 32 , 163–172.

White, H. D., & McCain, K. W. (1998). Visualizing a discipline: An author co-citation analysis of information science 1972–1995. Journal of the American Society for Information Science, 49 (4), 327–355.

Wouters, P., & Costas, R. (2012). Users, narcissism and control—Tracking the impact of scholarly publications in the 21st century. Report for the Surf Foundation .

Wuchty, S., Jones, B. F., & Uzzi, B. (2007). The increasing dominance of teams in production of knowledge. Science, 316 (5827), 1036–1039.

Yang, S. L., Han, R. Z., Wolfram, D., & Zhao, Y. H. (2016). Visualizing the intellectual structure of information science (2006–2015): Introducing author keyword coupling analysis. Journal of Informetrics, 10 (1), 132–150.

Yang, S. L., & Wang, F. F. (2015). Visualizing information science: Author direct citation analysis in China and around the world. Journal of Informetrics, 9 (1), 208–225.

Zhang, J. A., Vogeley, M. S., & Chen, C. M. (2011). Scientometrics of big science: A case study of research in the Sloan Digital Sky Survey. Scientometrics, 86 (1), 1–14.

Zhao, D. Z., & Strotmann, A. (2008a). Evolution of research activities and intellectual influences in information science 1996–2005: Introducing author bibliographic-coupling analysis. Journal of the American Society for Information Science and Technology, 59 (13), 2070–2086.

Zhao, D. Z., & Strotmann, A. (2008b). Information science during the first decade of the web: an enriched author co-citation analysis. Journal of the American Society for Information Science and Technology, 59 (6), 916–937.

Zhao, D. Z., & Strotmann, A. (2008c). Comparing all-author and first-author co-citation analyses of information science. Journal of Informetrics, 2 (3), 229–239.

Zhao, D. Z., & Strotmann, A. (2014). The knowledge base and research front of information science 2006–2010: An author cocitation and bibliographic coupling analysis. Journal of the Association for Information Science and Technology, 65 (5), 995–1006.

Zhao, Y. H., & Zhao, R. Y. (2016). An evolutionary analysis of collaboration networks in scientometrics. Scientometrics, 107 (2), 759–772.

Download references

Acknowledgements

We would like to thank the editor and reviewers. This research was supported by the National Social Science Foundation of China under Grant 17BGL031.

Author information

Authors and affiliations.

Research Center of Science Technology and Society, Dalian University, Dalian, 116622, China

Jianhua Hou

College of Information Engineering, Dalian University, Dalian, 116622, China

Xiucai Yang

College of Computing and Informatics, Drexel University, 3141 Chestnut Street, Philadelphia, PA, 19104-2875, USA

Chaomei Chen

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Jianhua Hou .

Rights and permissions

Reprints and permissions

About this article

Hou, J., Yang, X. & Chen, C. Emerging trends and new developments in information science: a document co-citation analysis (2009–2016). Scientometrics 115 , 869–892 (2018). https://doi.org/10.1007/s11192-018-2695-9

Download citation

Received : 21 August 2017

Published : 07 March 2018

Issue Date : May 2018

DOI : https://doi.org/10.1007/s11192-018-2695-9

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Information science
  • Information visualization
  • Co-citation analysis
  • Find a journal
  • Publish with us
  • Track your research
  • iSchool Connect

Research Areas

Archives and preservation.

Protecting and maintaining collections and materials in archives

Argumentation

Studying the construction of scientific arguments, including the use of information, evidence, and persuasion

Artificial Intelligence and Machine Learning

Researching the models, methods, uses, and impact of intelligent systems design for processing data and information

Community Informatics

Understanding how local communities and people in their everyday lives use and might use information technology, in libraries and elsewhere

Computational Social Science, Social Computing

Using computational methods to study and model social systems and user behaviors

Computing for Social Good

Understanding computing's potential for good (and harm), including the role of computing and technology in responding to social, ecological, political, and other challenges

Cultural Informatics and Heritage

Understanding the role of information technology in preserving, transmitting, and shaping human culture and heritage

Data Analytics and Human Centered Data

Using computational methods to transform both structured and unstructured data into actionable knowledge; and to understand and enable humans to explore and gain insight from vast data sets

Data Curation

Active and on-going management of data through its lifecycle of interest and usefulness to scholarship, science, and education

Data Science

Using statistical and computational techniques to discover and extract knowledge from structured and unstructured data.

Design and Evaluation of Information Systems and Services

Understanding the problems with existing information systems and services, and making them more effective and easier to use

Digital Humanities

Applying computing or using digital media in the humanities disciplines

Digital Libraries

Studying how to most effectively store, structure, retrieve, interpret and preserve collections of digital objects to serve a particular community or communities

Diversity and Social Justice

Addressing challenging, but necessary, topics such as racism, privilege, power, etc., and coupling them with critical theory in an effort to develop compassionate, proactive, and culturally competent information professionals

Education of Information Professionals

Evaluating the content of curricula and the methods for educating information professionals

Ethics and Values for Information

Assessing principles and standards that govern access to information

FATE (fairness, accountability, transparency, ethics)

Researching the complex social implications of AI, machine learning, data science, large-scale experimentation, and increasing automation; and developing computational techniques that draw on the deeper context surrounding these issues from sociology, history, and science and technology studies

Foundations of Information

Asking and answering the most basic and fundamental questions on the nature and uses of information resources

Health, Medical, and Bio-Informatics

Collecting and analyzing biological, medical, and health information

History of Information

Exploring the long history of  information helps us understand the effects of information technologies, systems, and practices on society and their implications for the future

Human Computer Interaction, User Experience, Computer Supported Cooperative Work

Investigating the use of computers to support individual use; and investigating the use of computers and networked technologies to support small-group and human-to-human communication and its impact on collaboration

Information Access

Recognizing the issues with information access and the methods in which individuals and groups access information

Information Literacy

Information literacy is an important skillset that enables individuals to locate, contextualize, evaluate, effectively use, and appropriately communicate information in a variety of different formats

Information Policy

Examining the set of rules, laws, or regulations that affect the creation, process, use, and destruction of information

Information Practices and Behaviors

Discovering and explicating how people seek, use, avoid, and share information to advance knowledge, aid in decision making, solve problems, and engage in everyday life activities

Information Retrieval

Finding relevant documents and other information resources to satisfy an information need or desire

Information Visualization

Studying the visual representation of abstract data 

Informetrics and Scientometrics

Studying the quantitative aspects of information and the quantitative features and characteristics of science and scientific research

Knowledge Representation, Ontologies

Research related to semantic networks, formal logic, frame-based systems; and how the beliefs, intentions, and value judgments of an intelligent agent (AI) can be expressed in a transparent, symbolic notation suitable for automated reasoning

Libraries and Librarianship

Research related to the assessment, management, development, and delivery of services provided by professional librarians in libraries and similar information institutions

Natural Language Processing, Text Mining, Text Analysis, Computational Linguistics

Examining the process of transforming unstructured text into structured data for use

Network Science and Network Analysis

Representing, analyzing, and modeling the structure and dynamics of complex social, scientific, and technological systems as networks or graphs; and using computational tools for identifying, explaining, and understanding the patterns they contain

Organization of Knowledge and Information

Bringing structure to the record of human culture and our accounts of the natural and social world

Privacy, Security, and Trust

Studying the intersection of privacy, security, and trust with information systems

Reproducibility

Analyzing the challenges to and environments favorable to fostering reproducible research

Science of Science

Using data to study, understand, and quantify the mechanisms underlying scientific research

Semantic Computing and Technologies

Studying the structure, design, and manipulation of computer content and technologies (e.g., AI, natural language, software engineering) to better satisfy the needs and intentions of users and to create a more meaningful user experience

Social and Information Networks

Understanding the intersection between social networks and information networks

Social Informatics

Examining the social aspects of information technology and how social issues affect the organization of information

Social Media

Understanding how and why people use social media, and how it impacts access and dissemination of information

Youth Literature, Culture, and Services

Analyzing library and information practices, preferences, and play for children, youth, tweens, and teens

newjerseystatemuseum.org |

research topics on information science

Research paper topics in library and information science

A systematic approach is best when undertaking research in the library and information science. Not only should you have an in-depth knowledge of major themes in the area, but you should also be aware of current research methods and topics of influence, such as library systems, cooperation between libraries, and the flow of information between libraries.

Finding a good research paper topic can greatly depend upon your interests and what you took away from your coursework. Paying attention in classes and taking adequate notes makes it easier to assimilate that knowledge into a coherent research paper topic. Take a look at the following research paper topics for some ideas:

  • A critical analysis of student attitudes towards cataloguing and classification in college campus libraries
  • The Impact of Public Libraries at the state level
  • The implementation of information and communication technology in academic libraries in Brazil
  • Evaluating the effect of feminization and professionalization on librarianship
  • The challenges involved in running private libraries in Nigeria
  • Defining comparative and international library and information science
  • An assessment of international cultural exchange through libraries
  • The role of international librarianship in promoting freedom of information and expression
  • International issues faced by librarians and information science professionals with regard to the knowledge society
  • Exploring the relationship between government schools and public libraries in the context of South Asia
  • The importance of resource-sharing in an international library network: bridging gaps using modern technology
  • Tackling indigenous knowledge by adopting innovative tools and strategies
  • The influence of library aid in developing countries during globalization
  • A critical comparison of American librarianship and information science research in European countries
  • Learnings from major book acquisitions in American academic libraries
  • The expanding purview of American ideas in German public libraries
  • The British Council and its critical role in building bridges across the developing world

Browsing through sample topics in library and information science can help you brainstorm your own ideas more effectively. Take the time to scan such resources and choose a topic that you can convincingly discuss and analyze. A good source for potential research paper topics and paper help is mypaperwriter.com , also papers written by past students as well as reputed works in the field.

Copyright ©2017 - newjerseystatemuseum.org

ct-logo

Top 400 Information Technology Research Topics – Full Guide!

The field of IT is progressive and ever-changing due to the rapid development of hardware, software, and networking technologies. The demand for innovative research in IT has also continued to rise as businesses and organizations embrace digital systems and data-driven solutions. 

Understanding the salient areas of study in IT will help professionals keep up with changes that arise and enable organizations to leverage emerging technologies effectively. 

Cybersecurity, artificial intelligence, cloud computing , and big data analytics have emerged through IT research. These fundamental factors shape the modern technology landscape, giving rise to immense possibilities for boosting productivity, raising efficiency, and improving competitiveness across sectors. 

However, companies wanting to navigate the complexities of today’s digital age and exploit new technological advances must examine some of the latest IT research topics.

Understanding Information Technology Research

Table of Contents

In the world of technology, research is a compass that helps us navigate its convoluted evolutions. For instance, Information Technology (IT) research has been conducted in computer science, software engineering, data analytics, and cybersecurity.

IT research involves systematic inquiry to advance knowledge, problem-solving, and innovation. This includes conducting rigorous experiments and analyzing results to unveil new theories or approaches that improve technologies or bring breakthroughs.

Therefore, interdisciplinarity is at the core of IT research, with collaboration cutting across various disciplines. Whether using AI to reinforce cyber security or big data analytics in healthcare, collaboration leads to solutions to complex problems.

This is because IT research is changing rapidly due to technological advances. Thus, researchers need to be up-to-date to make meaningful contributions.

Ethics are involved so that technology can be responsibly deployed. The researchers grapple with privacy, security, bias, and equity issues to ensure technology benefits society.

As a result of this publication and conferences, which enable dissemination of findings, leading to further innovations, collaboration has supported progress, hence speeding it up.

Understanding IT research is vital for leveraging technology to address societal challenges and foster positive change.

Recommended Readings: “ Top 109+ Media Bias Research Topics | Full Guide! “.

Picking the Right Topic to Research: The Key to Finding New Things 

In the always-changing world of information technology, choosing the proper topic to research is like starting a smart path. It’s a big decision that sets where your hard work will go and how much your findings could mean.

Fitting with Industry Moves and Issues

Finding a research topic that fits current industry moves and big issues is important. By staying informed on the latest happenings and problems in the technology field, you can ensure your research stays useful and helps solve real-world troubles.

Growing Fresh Ideas and Practical Uses

Choosing a research topic that generates fresh ideas and practical applications is crucial. Your findings should not just add to school talks but also lead to real solutions that can be used in real situations, pushing technology forward and making work smoother.

Sparking Mind Curiosity and Excitement

Selecting a research topic that sparks your curiosity and excitement is essential. When you dive into an area that truly fascinates you, the research journey becomes more engaging, and your drive to uncover big insights is stronger.

Finding Gaps and Unexplored Areas

Finding gaps in existing knowledge or unexplored areas in the technology landscape can lead to big discoveries. Entering uncharted spaces can uncover fresh insights and meaningfully advance the field.

Considering Potential Wide Effect and Growth

Considering your research topic’s potential wide effect and growth is crucial. Will your findings have far-reaching effects across industries? Can your solutions grow and shift to address changing challenges? Evaluating these things can help you prioritize research areas with the greatest potential for big impact.

By carefully choosing the right research topic, you can open the door to discoveries, push technology forward, and contribute to the constant evolution of the technology information landscape.

Top 400 Information Technology Research Topics

The list of the top 400 information technology research topics is organized into different categories. Let’s examine it. 

Artificial Intelligence (AI) and Machine Learning (ML)

  • Easy AI: Explaining and Using
  • Group Learning: Getting Better Together
  • AI in Health: Diagnosing and Helping
  • Robots Learning on Their Own
  • Being Fair with Computers
  • Talking to Computers in Normal Language
  • AI Fighting Bad Guys on the Internet
  • AI Driving Cars: How Safe Is It?
  • Sharing What We’ve Learned with Other Machines
  • AI in Schools: Computers Learning About You

Cybersecurity and Encryption

  • Trusting Computers: How to Stay Safe
  • Keeping Secrets Safe with Fancy Math
  • Secret Codes Computers Use: Safe or Not?
  • Spy Games: Watching Out for Bad Stuff
  • Keeping Secrets, Even from Friends
  • Your Body as Your Password: Is It Safe?
  • Fighting Against Computer Ransomers
  • Keeping Your Secrets Secret, Even When Sharing
  • Making Sure Your Smart Stuff Isn’t Spying on You
  • Insuring Against Computer Bad Luck

Data Science and Big Data

  • Sharing Secrets: How to Be Safe
  • Watching the World in Real-Time
  • Big Data: Big Computers Handling Big Jobs
  • Making Data Pretty to Look At
  • Cleaning Up Messy Data
  • Predicting the Future with Numbers
  • Finding Patterns in Connected Dots
  • Keeping Your Secrets Safe in Big Data
  • Sharing Our Secrets Without Telling Anyone
  • Helping the Planet with Numbers

Cloud Computing

  • Computers Without a Home: Where Do They Live?
  • Keeping Computers Close to Home
  • Moving Our Stuff to New Homes
  • Juggling Many Clouds at Once
  • Making Computers That Live in the Cloud
  • Keeping Clouds Safe from Bad Guys
  • Keeping Clouds Safe from Sneaky Spies
  • Making Sure Clouds Do What They’re Supposed To
  • Computers Need Energy Too!
  • Making the Internet of Things Even Smarter

Internet of Things (IoT)

  • Smart Stuff Everywhere: How Does It Work?
  • Watching Out for Bad Stuff in Smart Things
  • Smart Stuff: Is It Safe?
  • Taking Care of Smart Toys
  • Making Smart Things That Don’t Need Batteries
  • Making Smart Factories Even Smarter
  • Smart Cities: Making Cities Better Places to Live
  • Your Clothes Can Be Smart, Too!
  • Helping Farmers with Smart Farming
  • Keeping Secrets Safe in Smart Stuff

Human-Computer Interaction (HCI)

  • Magic Glasses: How Do They Work?
  • Making Computers Easy to Use
  • Making Computers for Everyone
  • Talking to Computers with Your Hands
  • Making Sure Computers Are Nice to People
  • Talking to Computers with Your Voice
  • Playing with Computers, You Can Touch
  • Trusting Computers to Drive for Us
  • Computers That Understand Different People
  • Making Computers That Read Our Minds

Software Engineering

  • Making Computers Work Together Smoothly
  • Building Computers from Tiny Pieces
  • Playing Games to Make Computers Better
  • Making Sure Computers Work Right
  • Making Old Computers New Again
  • Making Computers Like to Exercise
  • Making Computers Easier to Understand
  • Building Computers with Blueprints
  • Making Sure Computers Don’t Get Sick
  • Sharing Computer Secrets with Everyone

Mobile Computing

  • Keeping Phones Safe from Bad Guys
  • Making Apps for Every Kind of Phone
  • Keeping Phones Safe in the Cloud
  • Finding Your Way with Your Phone
  • Paying with Your Phone: Safe or Not?
  • Checking Your Health with Your Phone
  • Seeing the World Through Your Phone
  • Wearing Your Phone on Your Wrist
  • Learning on the Go with Your Phone
  • Making Phones Even Smarter with Clouds

Networking and Communications

  • Making Sure Computers Can Talk to Each Other
  • Making Computers Work Together Without Wires
  • Making the Internet Faster for Everyone
  • Getting More Internet Addresses for More Computers
  • Cutting the Internet into Pieces
  • Making the Internet Even More Invisible
  • Talking to Computers with Light
  • Making Sure Tiny Computers Talk to Each Other
  • Sending Messages Even When It’s Hard
  • Making the Radio Smarter for Computers

Bioinformatics and Computational Biology

  • Reading Your DNA with Computers
  • Making Medicine Just for You
  • Meeting the Microscopic World with Computers
  • Building Computer Models of Living Things
  • Finding New Medicine with Computers
  • Building Computer Models of Tiny Machines
  • Making Family Trees for Living Things
  • Counting Germs with Computers
  • Making Big Lists of Living Things
  • Making Computers Think Like Brains

Quantum Computing

  • Making Computers Better at Some Math Problems
  • Keeping Computers Safe from Small Mistakes
  • Making Computers Even Harder to Spy On
  • Making Computers Learn Faster with Quantum Tricks
  • Making Fake Worlds for Computers to Explore
  • Building Computers from Super-Cold Stuff
  • Making Computers Cold to Think Better
  • Making Computers Think Like Chemists
  • Making the Internet Even Safer with Computers
  • Showing Off What Computers Can Do Best

Green Computing

  • Saving Energy with Computers
  • Using Wind and Sun to Power Computers
  • Making Phones Last Longer Without Plugging In
  • Making Computers Kinder to the Planet
  • Recycling Old Computers to Save the Earth
  • Computers That Care About Their Trash
  • Saving Energy in Big Rooms Full of Computers
  • Making Computers Save Energy and Work Faster
  • Counting the Trash from Computers
  • Making Computers Kinder to the Planet’s Air

Information Systems

  • Making Computers Work Together in Big Companies
  • Making Computers Remember Their Friends
  • Making Computers Share What They Know
  • Making Computers Smart About Money
  • Making Computers Send Presents to Their Friends
  • Helping Computers Make Big Decisions
  • Making Government Computers Talk to Each Other
  • Making Computers Count Likes and Shares
  • Assisting computers to Find What You Asked For
  • Assisting companies to Keep Their Friends Happy

Semantic Web and Linked Data

  • Making Computers Understand Each Other Better
  • Making Computers Talk About Themselves
  • Making the Internet More Friendly for Computers
  • Helping Computers Find What They Need
  • Making Computers Smarter by Talking to Each Other
  • Making Computers Friends with Different Languages
  • Making Computers Understand Different Ideas
  • Making Computers Think Like Us
  • Making Computers Smarter About Old Stuff
  • Making Computers Share Their Secrets Safely

Social Computing and Online Communities

  • Making Friends on the Internet
  • Getting Good Suggestions from the Internet
  • Making Computers Work Together to Solve Problems
  • Learning from Your Friends on the Internet
  • Stopping Fake News on the Internet
  • Knowing How People Feel on the Internet
  • Helping Each Other on the Internet During Emergencies
  • Making Sure Computers Are Nice to Everyone
  • Keeping Secrets on the Internet
  • Making the Internet a Better Place for Everyone

Game Development and Virtual Worlds

  • Making Games That Play Fair
  • Letting Computers Make Their Fun
  • Making Fake Worlds for Fun
  • Learning with Games
  • Making the Rules for Fun
  • Watching How People Play Together
  • Seeing Things That Aren’t There
  • Letting Lots of People Play Together
  • Making the Engines for Fun
  • Playing Games to Learn

E-Learning and Educational Technology

  • Making Learning Easy for Everyone
  • Taking Classes on the Internet
  • Learning from Your Computer’s Teacher
  • Learning from What Computers Know
  • Learning Anywhere with Your Computer
  • Making Learning Fun with Games
  • Learning Without a Real Lab
  • Learning with Free Stuff on the Internet
  • Mixing School with Your Computer
  • Making School More Fun with Your Computer

Digital Forensics and Incident Response

  • Solving Computer Mysteries
  • Looking for Clues in Computers
  • Finding Bad Guys on the Internet
  • Looking for Clues on Phones and Tablets
  • Hiding Clues on Computers
  • Helping When Computers Get Sick
  • Solving Mysteries While the Computer Is On
  • Finding Clues on Your Smart Watch
  • Finding Tools for Finding Clues
  • Following the Rules When Solving Mysteries

Wearable Technology and Smart Devices

  • Keeping Healthy with Smart Watches
  • Making Clothes That Talk to Computers
  • Listening to the Earth with Your Shirt
  • Wearing Glasses That Show Cool Stuff
  • Making Your Home Smarter with Your Phone
  • Using Your Body to Unlock Your Phone
  • Helping People Move with Special Shoes
  • Assisting people to See with Special Glasses
  • Making Your Clothes Do More Than Keep You Warm
  • Keeping Secrets Safe on Your Smart Stuff

Robotics and Automation

  • Making Friends with Robots
  • Letting Robots Do the Hard Work
  • Robots That Work Together Like Ants
  • Learning Tricks from People
  • Robots That Feel Like Jelly
  • Helping Doctors and Nurses with Robots
  • Robots That Help Farmers Grow Food
  • Making Cars Without People
  • Teaching Robots to Recognize Things
  • Robots That Learn from Animals

Health Informatics

  • Computers That Help Doctors Keep Track of Patients
  • Sharing Secrets About Your Health with Other Computers
  • Seeing the Doctor on Your Computer
  • Keeping Track of Your Health with Your Phone
  • Making Medicine Better with Computers
  • Keeping Your Health Secrets Safe with Computers
  • Learning About Health with Computers
  • Keeping Health Secrets Safe on the Internet
  • Watching Out for Germs with Computers
  • Making Sure the Doctor’s Computer Plays Nice

Geographic Information Systems (GIS)

  • Watching the World Change with Computers
  • Making Maps on the Internet
  • Seeing the World from Very Far Away
  • Finding Hidden Patterns with Computers
  • Making Cities Better with Computers
  • Keeping Track of the Earth with Computers
  • Keeping Track of Wild Animals with Computers
  • Making Maps with Everyone’s Help
  • Seeing the World in 3D
  • Finding Things on the Map with Your Phone

Knowledge Management

  • Helping Computers Remember Things
  • Making Computers Talk About What They Know
  • Finding Secrets in Big Piles of Data
  • Helping Companies Remember What They Know
  • Sharing Secrets with Computers at Work
  • Making Computers Learn from Each Other
  • Making Computers Talk About Their Friends
  • Making Companies Remember Their Secrets
  • Keeping Track of What Companies Know

Computational Linguistics and Natural Language Processing (NLP)

  • Finding Out How People Feel on the Internet
  • Finding Names and Places in Stories
  • Making Computers Talk to Each Other
  • Making Computers Answer Questions
  • Making Summaries for Busy People
  • Making Computers Understand Stories
  • Making Computers Understand Pictures and Sounds
  • Making Computers Learn New Words
  • Making Computers Remember What They Read
  • Making Sure Computers Aren’t Mean to Anyone

Information Retrieval and Search Engines

  • Finding Stuff on the Internet
  • Getting Suggestions from the Internet
  • Finding Stuff at Work
  • Helping Computers Find Stuff Faster
  • Making Computers Understand What You Want
  • Finding Stuff on Your Phone
  • Finding Stuff When You’re Moving
  • Finding Stuff Near Where You Are
  • Making Sure Computers Look Everywhere for What You Want

Computer Vision

  • Finding Stuff in Pictures
  • Cutting Up Pictures
  • Watching Videos for Fun
  • Learning from Lots of Pictures
  • Making Pictures with Computers
  • Finding Stuff That Looks Like Other Stuff
  • Finding Secrets in Medical Pictures
  • Finding Out If Pictures Are Real
  • Looking at People’s Faces to Know Them

Quantum Information Science

  • Making Computers Learn Faster with Tricks

Social Robotics

  • Robots That Help People Who Have Trouble Talking
  • Robots That Teach People New Things
  • Making Robots Work with People
  • Helping Kids Learn with Robots
  • Making Sure Robots Aren’t Mean to Anyone
  • Making Robots Understand How People Feel
  • Making Friends with Robots from Different Places
  • Making Sure Robots Respect Different Cultures
  • Helping Robots Learn How to Be Nice

Cloud Robotics

  • Making Robots Work Together from Far Away
  • Making Robots Share Their Toys
  • Making Robots Do Hard Jobs in Different Places
  • Making Robots Save Energy
  • Making Robots Play Together Nicely
  • Making Robots Practice Being Together
  • Making Sure Robots Play Fair
  • Making Robots Follow the Rules

Cyber-Physical Systems (CPS)

  • Making Robots Work Together with Other Things
  • Keeping Robots Safe from Small Mistakes
  • Keeping Factories Safe from Bad Guys
  • Making Sure Robots Respect Different People
  • Making Sure Robots Work Well with People
  • Keeping Robots Safe from Bad Guys
  • Making Sure Robots Follow the Rules

Biomedical Imaging

  • Taking Pictures of Inside You with Computers
  • Seeing Inside You with Computers
  • Cutting Up Pictures of Inside You
  • Finding Problems Inside You with Computers
  • Cutting Up Pictures and Putting Them Together
  • Counting Inside You with Pictures
  • Making Pictures to Help Doctors
  • Making Lists from Pictures Inside You
  • Making Sure Pictures of You Are Safe

Remote Sensing

  • Watching Earth from Far Away with Computers
  • Making Pictures of Earth Change
  • Taking Pictures from Very High Up
  • Watching Crops Grow with Computers
  • Watching Cities Grow with Computers
  • Watching Earth Change with Computers
  • Watching Earth from Far Away During Emergencies
  • Making Computers Work Together to See Earth
  • Putting Pictures of Earth Together
  • Making Sure Pictures of Earth Are Safe

Cloud Gaming

  • Playing Games from Far Away
  • Making Games Work Faster from Far Away
  • Keeping Games Safe from Bad Guys
  • Making Sure Everyone Can Play Together
  • Making Games Faster from Far Away
  • Watching People Play Games from Far Away
  • Making Sure Games Look Good from Far Away
  • Watching Games Get More Popular

Augmented Reality (AR)

  • Making Glasses That Show Cool Stuff
  • Making Cool Stuff for Glasses to Show
  • Watching Glasses Follow You
  • Watching Phones Show Cool Stuff
  • Making Cool Stuff to Show with Phones
  • Making Places Even Better with Phones
  • Making Factories Even Better with Glasses
  • Making Places Even Better with Glasses
  • Making Sure Glasses Don’t Scare Anyone

Virtual Reality (VR)

  • Making Glasses That Show Different Worlds
  • Making Glasses That Follow Your Hands
  • Making Therapy Fun with Glasses
  • Making Learning Fun with Glasses
  • Making Glasses That Make Jobs Safer
  • Making Glasses That Show Your Friends
  • Making Sure Glasses Are Friendly
  • Making Glasses That Make Buildings Better
  • Making Sure Glasses Aren’t Scary

Digital Twins

  • Making Computers That Copy the Real World
  • Making People Better with Computers
  • Making Flying Safer with Computers
  • Making Cars Safer with Computers
  • Making Energy Better with Computers
  • Making Buildings Better with Computers
  • Making Cities Safer with Computers
  • Making Sure Computers Copy the Real World Safely
  • Making Computers Follow the Rules

Edge Computing

  • Making Computers Work Faster Near You
  • Keeping Computers Safe Near You
  • Making Computers Work with Far-Away Computers
  • Making Computers Work Fast with You
  • Making Computers Work Together Near You
  • Making Phones Work Faster Near You
  • Making Computers Work Near You
  • Making Computers Work in Busy Places

Explainable AI (XAI)

  • Making Computers Explain What They Do
  • Making Medicine Safer with Computers
  • Making Money Safer with Computers
  • Making Computers Safe to Drive Cars
  • Making Computers Fair to Everyone
  • Making Computers Explain What They Think
  • Making Computers Easy to Understand

Blockchain and Distributed Ledger Technology (DLT)

  • Making Secret Codes Computers Use
  • Making Contracts Computers Can Understand
  • Making Computers Share Secrets Safely
  • Making Money Safe with Computers
  • Making Computers Work Together Nicely
  • Making Computers Keep Secrets Safe
  • Making Computers Work Together Fairly
  • Making Stuff Move Safely with Computers

Quantum Communication

  • Making Computers Talk to Each Other Safely
  • Making Computers Talk to Each Other from Far Away
  • Making Computers Talk to Each Other in Secret
  • Making Money Move Safely with Computers

This list covers a broad spectrum of topics within Information Technology, ranging from foundational concepts to cutting-edge research areas. Feel free to choose any topic that aligns with your interests and expertise for further exploration and study!

Emerging Trends in Information Technology Research

In the rapidly changing world of Computer Studies, keeping up with the latest trends is indispensable. Technology keeps changing, and so does research in computer studies. From awesome things like clever robots to how we can safeguard our online information, computer studies research is always discovering new ways to improve our lives. Therefore, let us delve into some of the most exciting new trends shaping computer studies’ future.

  • Smart Computers:

Right now, smart computers are a hot item. They can learn from experience, recognize patterns, and even understand language like humans do. This helps in many areas, such as healthcare or finance. So researchers are working on making smart computers smarter yet so that they can make decisions alone and be fair to everyone.

  • Fast Computing:

As more devices connect to the Internet, we need ways to process information quickly. Fast computing helps bring processing power closer to where the information comes from, making things quicker and more efficient. Thus, researchers have been figuring out how to improve fast computing, especially for analyzing real-time data.

  • Keeping Things Safe:

With all the cool tech around, keeping our information safe from bad guys is important. We must develop methods to safeguard our data and networks from cyber attackers. In addition, they have also been considering how to ensure the privacy of our personal information so that only authorized individuals can access it.

  • Fancy Computers:

The next big thing in computing is quantum computers. They can do calculations at a high speed that ordinary ones cannot. Researchers are working hard to achieve quantum computing because it could be useful in cracking codes and creating new drugs.

  • New Ways of Doing Things Together:

Blockchain is an exciting technology that allows us to collaborate without a central authority. Its use in cryptocurrencies is quite popular but it has other applications too. Blockchain can be applied for purposes such as helping us discover where products come from, proving who we are on the internet, and making contracts that cannot be changed later on.

  • Virtual Reality Adventures:

Entering a completely different world is what Virtual Reality (VR) and Augmented Reality (AR) do. The feeling of being in reality is what these two technologies create, which is not real. These researchers are working hard on making VRs and ARs better so that they can be used for learning, training, and amusement in more innovative ways.

In summary, computer studies research keeps changing with new trends such as smart computers, rapid computing, cybersecurity issues, high-end computers, collaboration platforms and immersive games or virtual reality escapades. 

By exploring these trends and developing new ideas, researchers ensure that technology keeps improving and making our lives easier and more exciting.

How can I brainstorm research topics in information technology?

Start by identifying your areas of interest and exploring recent advancements in the field. Consider consulting with mentors or peers for suggestions and feedback.

What are some ethical considerations in AI research?

Ethical considerations in AI research include fairness, transparency, accountability, and privacy. Researchers should ensure their algorithms and models do not perpetuate bias or harm individuals.

How can I stay updated on emerging trends in IT research?

Follow reputable journals, conferences, and online forums dedicated to information technology. Engage with the academic community through discussions and networking events.

Similar Articles

100 Research Topics In Commerce Field

Top 100 Research Topics In Commerce Field

The world of commerce is rapidly evolving. With new technologies, globalization, and changing consumer behaviors, many exciting research topics exist…

Mini Project Ideas For Computer Engineering Students

Top 30+ Mini Project Ideas For Computer Engineering Students

Mini projects are really important for computer engineering students. They help students learn by doing practical stuff alongside their regular…

Leave a Comment Cancel Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed .

  • Browse Works
  • Art & Humanities

Library and Information Science

Library and information science research papers/topics, underutilisation of internet facilities at universities a case study of jomo kenyatta memorial library (jkml) university of nairobi and united states international university africa (usiu a).

Description: A Project Report by Muthoni Dorothy Njiraine, Submitted in in Partial Fulfillment of the Requirement for the award of the Degree of Master of Science in Information Science of Makere University

Perspectives on Knowledge Management:: A Literature Review

Abstract: This paper is a study of theoretical perspectives on knowledge and Knowledge Management. Business organizations in the 21st century need effective Knowledge Management practices in order to enhance the performance and growth of their businesses and ensure long-term sustainability and competitive advantage. An understanding and appreciation of knowledge as a strategic resource is critical for organisational decision makers so that they can take Knowledge Management more seriously. T...

Motivation Cognitive and Behavioral Theories and Techniques

This paper describes Motivation: Cognitive and behavioral theories and techniques, it analyzed the three theories underlying the cognitive and behavioral theories and techniques, it examined the expectancy theory, assumptions underlying expectancy theory, the explanation, the applicability of the expectancy theory. It also examined the equity theory of motivation, gave an explanation of the equity theory, application of equity theory in an educational organization. It also examined the goal s...

A Critique of the paper ‘Library Architecture around the World’ by Garba, Chiwendu and Mustapha

For the past two decades, libraries have been dramatically reinventing their physical spaces. The traditional model of cavernous reading rooms and dark warrens separated by stacks of books is incompatible with the digital age. The library of today and tomorrow must provide versatile spaces that support a wide range of users’ learning and research activities while accommodating rapid advances in information technology (IT). As expectations for library resources and physical facilities have c...

How to Write an Empirical Review

The purpose of the paper is to offer guidance on how to write an empirical review. The paper presented an introduction, and discussed the concept of empirical review, the importance of empirical review, steps for writing empirical review, apractical approach to writing an empirical review, characteristics of a good empirical review and concluded with the following statement; well-crafted empirical reviews are the cornerstone of good papers, however it is not uncommon to find weak, or even abs...

Diversity of Information Services in the Library World

Regardless of which type of library and the environment it is designed to serve, the basic mission and objectives of information service provision should be to support and promote natural and social justice, equity, fair play and democratization of information access and utilization.  It is within this perspective that the Universal Declaration of Human Rights and the United Nations Convention on the Rights of Persons with Disabilities under the principles of non-discrimination, equal opport...

Controlled vocabulary

Virtually every common word in the English language has more than one meaning or senseand many of those senses have more than one nuance; many words can be used as nouns, verbs, adjectives, and/or adverbs. Search systems that purport to allow the use of natural language cannot yet successfully distinguish among different meanings or various parts of speech in very large general systems, although some progress has been made in narrow subject areas. 

Concepts of statistical analysis

In many fields of research, null hypothesis, significance tests, and p values are the accepted way of assessing the certainty with which research results can be extrapolated beyond the sample studied. The inevitable difficulties of statistical inference mean that these probabilities can only be tentative, but probabilities are the natural way to express uncertainties, so, arguably, researchers using statistical methods have an obligation to estimate how probable their hypotheses are by the be...

Concept of Information Retrieval and the Strategies

Information retrieval system (IRS) came into being as a means of ensuring that information generated and recorded do not get over time. Before knowledge became recorded, individuals formed the repository of knowledge. With libraries, repository of knowledge began to change into recorded form. 

An organized structure for vocabulary control

This paper examined the concept of controlled vocabulary, it gave the definition and discussed the major concerns in establishing a controlled vocabulary, the types of controlled vocabulary. The principles of creating vocabulary control, principles for applying controlled vocabulary, controlled vocabulary standards, mechanics of vocabulary control, the merits and demerits of vocabulary control, and vocabulary control challenges and their solutions, and other vocabulary control challenges. The...

A legal approach to indexing and Abstracting in academic libraries

The main aim of information is to get information at the right time. Therefore, this paper takes a legal approach to indexing and Abstracting in academic libraries. It generally takes an extensive look at the importance of indexing and abstracting as a tool for effective retrieval and dissemination of information in any academic library. 

A Critical Analysis of the Library of Congress

The Library of Congress houses the largest information resources, records and archival collection of materials in the world (Whitman, 2021). As part of the Library's mission to make its resources available and useful to the American public, the Library has digitized a number of these materials and has also created an array of online secondary sources that highlight life and work. 

Information Need and Seeking Behaviour of Pregnant Women in Ughelli General Hospital, Delta State

This paper examined the topic on information needs and seeking behaviour of Pregnant Women in Ughelli General Hospital, Delta State to this end therefore, the researcher came up with four objectives which are: to identify the information needs of pregnant women in ughelli general hospital, to ascertain the information seeking behaviour of pregnant women in ughelli general hospital, to identify the information sources used by pregnant women in ughelli general hospital, to identify challen...

Administration and Management of Digital Libraries: An Overview

This paper examined administration and management of digital libraries: an overview. The concept management was clearly defined and explained in the context o f the work; thereafter the term digital library was explained succinctly as an age that is characterized by efficient and effective conversion, storage, diffusion and dissemination of data to users. The various services that are performed in the digital environment were listed as follows: Circulation Services (Reader Services); Ser...

Knowledge and Access to Primary Health Care Information Among Women in Rural Setting

Primary health care center offer professional medical care for individuals based on a locality or community before shifting them to more advance hospital-based care. Unfortunately, few studies exist on Knowledge and access to primary health care information among women in rural area in developing countries. This study adopted interpretative paradigm and collected qualitative data using Dervin Sense-Making theory approach. The collected data were analyzed using inductive analytical processes. ...

Library and information Science Project Topics, thesis, seminars, research papers termpapers. Project topics in Library and information Science for students, undergraduates, MSc, HND, NCE.

Popular Papers/Topics

Strategies for combating book theft and vandalism in academic libraries (a case study of futo library), the importance of internet to students of academic institutions in nigeria (a case study of imo state univeristy owerri), the role of ict in the of reference services to library users in nigeria (a case study of imo state library), challenges in the education and training of library and information science students in nigerian, use of information and communication technology in academic libraries in nigeria (a case study of nnamdi azikiwe university awka), the effects of poor funding of public libaries in nigeria (a case study of imo state public library owerri), the role of ict in the effective management of students academic record (a case study of department of record and statistics federal polytechnic nekede), acquisition and management of serial in academic libraries in imo state (a case study of imo state university library), the relevance of ict in modern library setting of information and communication technology facilities in academic (a case study of federal university of technology library owerri), effects of poor implementation of collection development policy in academic libraries in imo state (a case study of federal polytechnic nekede owerri), evaluation of academic library services, the problems of acquisition of material and services to users in special libraries in nigeria (a case study of imo state house of assembly), the impact of information and communication technology (ict) in nigerian university libraries, choosing librarianship as a career choice by secondary school students (a case study of some selected secondary schools in lokoja metropolis), problems of book acquisition in academic libraries in imo state (a case study of imo state univeristy owerri (imsu)).

Privacy Policy | Refund Policy | Terms | Copyright | © 2024, Afribary Limited. All rights reserved.

Cart

  • SUGGESTED TOPICS
  • The Magazine
  • Newsletters
  • Managing Yourself
  • Managing Teams
  • Work-life Balance
  • The Big Idea
  • Data & Visuals
  • Reading Lists
  • Case Selections
  • HBR Learning
  • Topic Feeds
  • Account Settings
  • Email Preferences

How to Vet Information Before Making a Decision

  • Alex Edmans

research topics on information science

Four questions to ask when you’re considering the evidence.

The daily decisions modern leaders face are increasingly complex. But executives have a tool to combat these challenges – information. At the click of a mouse or the press of a thumb, they can call up cutting edge research on virtually any topic. With so much information available, how do we know what to trust? What executives need is a simple taxonomy of misinformation so they know what to look out for. Drawing on the tools of social science research we can categorize misinformation into four missteps. This framework can be useful to leaders of all kinds who need to ask better questions to manage their own information onslaughts.

The challenges facing business leaders have never been greater. Regular decisions are increasingly complex, given inflation, trade tensions, and political uncertainty. Human capital issues now include diversity, equity and inclusion, mental health, and upskilling for the fourth industrial revolution. Environmental, social and governance concerns can no longer be delegated to a corporate social responsibility department; they’re the duty of the C-suite. Artificial intelligence brings myriad new opportunities, but also multiple new threats.

research topics on information science

  • Alex Edmans is a Professor of Finance at London Business School, where he specializes in corporate finance, behavioral finance, and corporate social responsibility. He earned his BA from Oxford University and his Ph.D. from MIT, where he was a Fulbright scholar. He is the author of May Contain Lies: How Stories, Statistics, and Studies Exploit Our Biases – And What We Can Do About It (Penguin Random House, 2024).

Partner Center

share this!

June 26, 2024

This article has been reviewed according to Science X's editorial process and policies . Editors have highlighted the following attributes while ensuring the content's credibility:

fact-checked

peer-reviewed publication

trusted source

Sharing false political information on social media may be associated with positive schizotypy, research suggests

by Public Library of Science

Sharing false political information on social media may be associated with positive schizotypy

Sharing false political information on social media by users may be associated with aspects of personality such as positive schizotypy, a set of traits including paranoia, suspicion and disrupted thinking patterns. It may also be linked to a motivation to increase awareness according to a study published June 26, 2024 in the open-access journal PLOS ONE by Tom Buchanan, University of Westminster, UK, and colleagues.

The spread of false political information on social media can tarnish trust in authentic news and even contribute to social unrest. Knowingly or not, a small portion of social media users actively share false material.

Buchanan and colleagues asked what differentiates those who share false material on social media from those who do not and why they do it. To do this, they tested two categories of factors: individual user differences (like personality) as well as user motivation .

The researchers conducted four individual studies on a total of 1,916 US residents. Participants did not overlap between studies.

  • Study 1 used a cross-sectional online survey to explore the relationship between individual differences (e.g., positive schizotypy, conscientiousness and decision-making style) and users' self-reported tendency to share false information.
  • Study 2 expanded on Study 1 by surveying respondents' motivations for sharing false information (e.g., activism, manipulation, and entertainment).
  • In Study 3, participants (whose individual differences and motivations were surveyed) viewed a series of true and false political headlines, and were asked to indicate whether they would consider sharing each and whether each was truthful.
  • In Study 4, the researchers assessed real Tweets posted by participants to determine if the factors identified in Study 1, 2 and 3 are associated with actual sharing of false material on Twitter.

Across all studies, the researchers found evidence that positive schizotypy is related to sharing false information, both accidentally and deliberately, though they note that the effect sizes are small. This might be because positive schizotypy is associated with decision-making based more on intuition—and sometimes biases—rather than reflective/deliberate thought, though the researchers suspect the mechanism may be complex. As for motivations, participants most commonly reported sharing political information for reasons of "raising awareness."

The researchers noted limitations of their studies: small sample sizes in some cases limited the exploratory analysis that could be performed, and participants may not always have known whether or not the information they shared was false.

A better understanding of who shares false information and why may help in identifying and developing targeted strategies to combat the spread of misinformation, the researchers say. They also suggest further research is needed to understand the links between positive schizotypy and spread of misinformation.

The authors add, "We've all seen false political information on social media, but only a few of us choose to share it. This study showed that our specific motivations for sharing, as well as our individual psychological characteristics, are associated with sharing false material both accidentally and on purpose."

Journal information: PLoS ONE

Provided by Public Library of Science

Explore further

Feedback to editors

research topics on information science

The demonstration of vacuum levitation and motion control on an optical-electrostatic chip

26 minutes ago

research topics on information science

True scale of carbon impact from long-distance travel revealed

2 hours ago

research topics on information science

Aboriginal ritual passed down over 12,000 years, cave find shows

research topics on information science

Increased atmospheric moisture may dampen the 'seeds' of hurricanes

14 hours ago

research topics on information science

Researchers train sheep to complete awake MRI imaging

15 hours ago

research topics on information science

Research intern helps discover a new pulsar buried in a mountain of data

16 hours ago

research topics on information science

Genetic patterns of world's farmed, domesticated foxes revealed via historical deep-dive

research topics on information science

Study finds one-third of Indonesia's deforested land left idle

research topics on information science

Microscopic fungi enhance soil carbon storage in new landscapes created by shrinking Arctic glaciers

research topics on information science

Rethinking old reaction mechanisms to obtain drug-type molecules

Relevant physicsforums posts, cover songs versus the original track, which ones are better.

9 hours ago

Who is your favorite Jazz musician and what is your favorite song?

Biographies, history, personal accounts.

Jun 30, 2024

Today's Fusion Music: T Square, Cassiopeia, Rei & Kanade Sato

Jun 29, 2024

The Balinese Alphabet

Jun 27, 2024

History of Railroad Safety - Spotlight on current derailments

Jun 26, 2024

More from Art, Music, History, and Linguistics

Related Stories

research topics on information science

Some people who share fake news on social media actually think they're helping the world, say researchers

Jan 18, 2024

research topics on information science

How to reduce the spread of fake news—by doing nothing

Dec 18, 2020

research topics on information science

This simple trick could help stop the spread of misinformation on social media

Feb 12, 2020

research topics on information science

Stemming the spread of misinformation on social media

Jul 2, 2020

research topics on information science

On social media, most people do care about accurate news but need reminders not to spread misinformation: study

Mar 17, 2021

research topics on information science

Spotting hoaxes: How young people use cues to spot misinformation online

May 26, 2021

Recommended for you

research topics on information science

The beginnings of fashion: Paleolithic eyed needles and the evolution of dress

Jun 28, 2024

research topics on information science

Study finds motivation to compete is stronger with in-group members than with outsiders

research topics on information science

We date and marry people who are attractive as we are, new analysis finds

research topics on information science

Lie-detection AI could provoke people into making careless accusations, researchers warn

research topics on information science

How the Meta algorithm influences election advertising

research topics on information science

Reframing voting as 'duty to others' could be key to increasing engagement, turnout

Jun 21, 2024

Let us know if there is a problem with our content

Use this form if you have come across a typo, inaccuracy or would like to send an edit request for the content on this page. For general inquiries, please use our contact form . For general feedback, use the public comments section below (please adhere to guidelines ).

Please select the most appropriate category to facilitate processing of your request

Thank you for taking time to provide your feedback to the editors.

Your feedback is important to us. However, we do not guarantee individual replies due to the high volume of messages.

E-mail the story

Your email address is used only to let the recipient know who sent the email. Neither your address nor the recipient's address will be used for any other purpose. The information you enter will appear in your e-mail message and is not retained by Phys.org in any form.

Newsletter sign up

Get weekly and/or daily updates delivered to your inbox. You can unsubscribe at any time and we'll never share your details to third parties.

More information Privacy policy

Donate and enjoy an ad-free experience

We keep our content available to everyone. Consider supporting Science X's mission by getting a premium account.

E-mail newsletter

Numbers, Facts and Trends Shaping Your World

Read our research on:

Full Topic List

Regions & Countries

  • Publications
  • Our Methods
  • Short Reads
  • Tools & Resources

Read Our Research On:

Public Trust in Government: 1958-2024

Public trust in the federal government, which has been low for decades, has increased modestly since 2023 . As of April 2024, 22% of Americans say they trust the government in Washington to do what is right “just about always” (2%) or “most of the time” (21%). Last year, 16% said they trusted the government just about always or most of the time, which was among the lowest measures in nearly seven decades of polling.

Date.Individual pollsMoving average
5/19/2024PEW2222
6/11/2023PEW1619
5/01/2022PEW2020
4/11/2021PEW2421
8/2/2020PEW2024
4/12/2020PEW2721
3/25/2019PEW1717
12/04/2017PEW1818
4/11/2017PEW2019
10/04/2015PEW1918
7/20/2014CNN1419
2/26/2014PEW2418
11/15/2013CBS/NYT1720
10/13/2013PEW1919
5/31/2013CBS/NYT2020
2/06/2013CBS/NYT2022
1/13/2013PEW2623
10/31/2012NES2219
10/19/2011CBS/NYT1017
10/04/2011PEW2015
9/23/2011CNN1518
8/21/2011PEW1921
2/28/2011PEW2923
10/21/2010CBS/NYT2223
10/01/2010CBS/NYT1821
9/06/2010PEW2423
9/01/2010CNN2523
4/05/2010CBS/NYT2023
4/05/2010PEW2522
3/21/2010PEW2224
2/12/2010CNN2622
2/05/2010CBS/NYT1921
1/10/2010GALLUP1920
12/20/2009CNN2021
8/31/2009CBS/NYT2422
6/12/2009CBS/NYT2023
12/21/2008CNN2625
10/15/2008NES3124
10/13/2008CBS/NYT1724
7/09/2007CBS/NYT2424
1/09/2007PEW3128
10/08/2006CBS/NYT2929
9/15/2006CBS/NYT2830
2/05/2006PEW3431
1/20/2006CBS/NYT3233
1/06/2006GALLUP3232
12/02/2005CBS/NYT3232
9/11/2005PEW3131
9/09/2005CBS/NYT2930
6/19/2005GALLUP3035
10/15/2004NES4639
7/15/2004CBS/NYT4041
3/21/2004PEW3638
10/26/2003GALLUP3736
7/27/2003CBS/NYT3643
10/15/2002NES5546
9/04/2002GALLUP4646
9/02/2002CBS/NYT3840
7/13/2002CBS/NYT3840
6/17/2002GALLUP4443
1/24/2002CBS/NYT4646
12/07/2001CBS/NYT4849
10/25/2001CBS/NYT5554
10/06/2001GALLUP6049
1/17/2001CBS/NYT3144
10/31/2000CBS/NYT4038
10/15/2000NES4442
7/09/2000GALLUP4239
4/02/2000ABC/POST3138
2/14/2000PEW4034
10/03/1999CBS/NYT3036
9/14/1999CBS/NYT3833
5/16/1999PEW3133
2/21/1999PEW3131
2/12/1999ABC/POST3232
2/04/1999GALLUP3334
1/10/1999CBS/NYT3734
1/03/1999CBS/NYT3337
12/01/1998NES4033
11/15/1998PEW2630
11/01/1998CBS/NYT2426
10/26/1998CBS/NYT2628
8/10/1998ABC/POST3431
2/22/1998PEW3435
2/01/1998GALLUP3933
1/25/1998CBS/NYT2632
1/19/1998ABC/POST3132
10/31/1997PEW3931
8/27/1997ABC/POST2231
6/01/1997GALLUP3226
1/14/1997CBS/NYT2327
11/02/1996CBS/NYT2527
10/15/1996NES3328
5/12/1996GALLUP2731
5/06/1996ABC/POST3429
11/19/1995ABC/POST2527
8/07/1995GALLUP2222
8/05/1995CBS/NYT2021
3/19/1995ABC/POST2220
2/22/1995CBS/NYT1821
12/01/1994NES2221
10/29/1994CBS/NYT2222
10/23/1994ABC/POST2220
6/06/1994GALLUP1719
1/30/1994GALLUP1920
1/20/1994ABC/POST2422
3/24/1993GALLUP2225
1/17/1993ABC/POST2825
1/14/1993CBS/NYT2425
10/23/1992CBS/NYT2225
10/15/1992NES2925
6/08/1992GALLUP2329
10/20/1991ABC/POST3535
3/06/1991CBS/NYT4742
3/01/1991ABC/POST4546
1/27/1991ABC/POST4640
12/01/1990NES2833
10/28/1990CBS/NYT2532
9/06/1990ABC/POST4235
1/16/1990ABC/POST3838
6/29/1989CBS/NYT3539
1/15/1989CBS/NYT4441
11/10/1988CBS/NYT4443
10/15/1988NES4141
1/23/1988ABC/POST3940
10/18/1987CBS/NYT4143
6/01/1987ABC/POST4743
3/01/1987CBS/NYT4244
1/21/1987CBS/NYT4343
1/19/1987ABC/POST4442
12/01/1986NES3944
11/30/1986CBS/NYT4943
9/09/1986ABC/POST4044
1/19/1986CBS/NYT4244
11/06/1985CBS/NYT4943
7/29/1985ABC/POST3842
3/21/1985ABC/POST3740
2/27/1985CBS/NYT4642
2/22/1985ABC/POST4345
11/14/1984CBS/NYT4644
10/15/1984NES4441
12/01/1982NES3339
11/07/1980CBS/NYT3932
10/15/1980NES2530
3/12/1980CBS/NYT2627
11/03/1979CBS/NYT3028
12/01/1978NES2931
10/23/1977CBS/NYT3332
4/25/1977CBS/NYT3534
10/15/1976NES3336
9/05/1976CBS/NYT4035
6/15/1976CBS/NYT3335
3/01/1976GALLUP3334
2/08/1976CBS/NYT3635
12/01/1974NES3636
10/15/1972NES5353
12/01/1970NES5454
10/15/1968NES6262
12/01/1966NES6565
10/15/1964NES7777
12/01/1958NES7373

When the National Election Study began asking about trust in government in 1958, about three-quarters of Americans trusted the federal government to do the right thing almost always or most of the time.

Trust in government began eroding during the 1960s, amid the escalation of the Vietnam War, and the decline continued in the 1970s with the Watergate scandal and worsening economic struggles.

Confidence in government recovered in the mid-1980s before falling again in the mid-’90s. But as the economy grew in the late 1990s, so too did trust in government. Public trust reached a three-decade high shortly after the 9/11 terrorist attacks but declined quickly after. Since 2007, the shares saying they can trust the government always or most of the time have not been higher than 30%.

Today, 35% of Democrats and Democratic-leaning independents say they trust the federal government just about always or most of the time, compared with 11% of Republicans and Republican leaners.

Democrats report slightly more trust in the federal government today than a year ago. Republicans’ views have been relatively unchanged over this period.

Since the 1970s, trust in government has been consistently higher among members of the party that controls the White House than among the opposition party.

Republicans have often been more reactive than Democrats to changes in political leadership, with Republicans expressing much lower levels of trust during Democratic presidencies. Democrats’ attitudes have tended to be somewhat more consistent, regardless of which party controls the White House.

However, Republican and Democratic shifts in attitudes from the end of Donald Trump’s presidency to the start of Joe Biden’s were roughly the same magnitude.

Date.Democrat/Lean DemRepublican/Lean Rep
5/19/2024PEW3511
6/11/2023PEW258
5/1/2022PEW299
4/11/2021PEW369
8/2/2020PEW1228
4/12/2020PEW1836
3/25/2019PEW1421
12/04/2017PEW1522
4/11/2017PEW1528
10/04/2015PEW2611
7/20/2014CNN1711
2/26/2014PEW3216
11/15/2013CBS/NYT318
10/13/2013PEW2710
5/31/2013CBS/NYT308
2/06/2013CBS/NYT348
1/13/2013PEW3715
10/31/2012NES2916
10/19/2011CBS/NYT138
10/04/2011PEW2712
9/23/2011CNN2011
8/21/2011PEW2513
3/01/2011PEW3424
10/21/2010CBS/NYT367
10/01/2010CBS/NYT2713
9/06/2010PEW3513
9/01/2010CNN3118
4/05/2010CBS/NYT2714
3/21/2010PEW3213
2/12/2010CNN3418
2/05/2010CBS/NYT319
1/10/2010GALLUP2316
12/20/2009CNN2516
8/31/2009CBS/NYT3412
6/12/2009CBS/NYT3510
12/21/2008CNN3022
10/15/2008NES3431
10/13/2008CBS/NYT1219
7/09/2007CBS/NYT1831
1/09/2007PEW2243
10/08/2006CBS/NYT2050
9/15/2006CBS/NYT2044
2/05/2006PEW2053
1/20/2006CBS/NYT2351
1/06/2006GALLUP2044
12/02/2005CBS/NYT1952
9/11/2005PEW1949
9/09/2005CBS/NYT2142
6/19/2005GALLUP2436
10/15/2004NES3561
3/21/2004PEW2455
10/26/2003GALLUP3542
7/27/2003CBS/NYT2551
10/15/2002NES5263
9/04/2002GALLUP3855
9/02/2002CBS/NYT3252
7/13/2002CBS/NYT3445
6/17/2002GALLUP3355
1/24/2002CBS/NYT3956
12/07/2001CBS/NYT3960
10/25/2001CBS/NYT4770
10/06/2001GALLUP5268
1/17/2001CBS/NYT2638
10/15/2000NES4843
7/09/2000GALLUP4241
4/02/2000ABC/POST3824
2/14/2000PEW4637
10/03/1999CBS/NYT3127
9/14/1999CBS/NYT4235
5/16/1999PEW3630
2/21/1999PEW3525
2/12/1999ABC/POST4121
2/04/1999GALLUP3829
1/10/1999CBS/NYT4233
1/03/1999CBS/NYT3729
12/01/1998NES4535
11/19/1998PEW3123
11/01/1998CBS/NYT2822
10/26/1998CBS/NYT2825
8/10/1998ABC/POST4030
2/22/1998PEW4228
2/01/1998GALLUP5226
1/25/1998CBS/NYT3122
10/31/1997PEW4632
6/01/1997GALLUP3925
1/14/1997CBS/NYT2920
11/02/1996CBS/NYT3120
10/15/1996NES4027
5/12/1996GALLUP3220
5/06/1996ABC/POST4135
11/19/1995ABC/POST2726
8/07/1995GALLUP2421
8/05/1995CBS/NYT2020
3/19/1995ABC/POST2720
2/22/1995CBS/NYT1819
12/01/1994NES2618
10/29/1994CBS/NYT2619
10/23/1994ABC/POST2716
6/06/1994GALLUP2311
1/30/1994GALLUP2514
1/20/1994ABC/POST3018
3/24/1993GALLUP3211
1/17/1993ABC/POST3225
1/14/1993CBS/NYT2621
10/23/1992CBS/NYT1731
10/15/1992NES3134
6/08/1992GALLUP1731
10/20/1991ABC/POST3141
3/06/1991CBS/NYT4056
3/01/1991ABC/POST4152
12/01/1990NES2632
10/28/1990CBS/NYT2131
9/06/1990ABC/POST3748
1/16/1990ABC/POST3246
6/29/1989CBS/NYT2745
1/15/1989CBS/NYT3754
11/10/1988CBS/NYT3658
10/15/1988NES3551
1/23/1988ABC/POST3151
10/18/1987CBS/NYT3647
6/01/1987ABC/POST3859
3/01/1987CBS/NYT3454
1/21/1987CBS/NYT3651
1/19/1987ABC/POST3951
12/01/1986NES3153
11/30/1986CBS/NYT3763
9/09/1986ABC/POST3051
1/19/1986CBS/NYT3651
11/06/1985CBS/NYT4259
7/29/1985ABC/POST3048
3/21/1985ABC/POST2949
2/22/1985ABC/POST3062
11/14/1984CBS/NYT3659
10/15/1984NES4150
12/01/1982NES3241
11/07/1980CBS/NYT4042
10/15/1980NES3123
3/12/1980CBS/NYT3022
11/03/1979CBS/NYT3228
12/01/1978NES3326
10/23/1977CBS/NYT4025
4/25/1977CBS/NYT3734
10/15/1976NES3042
9/05/1976CBS/NYT3845
6/15/1976CBS/NYT3636
3/01/1976GALLUP3140
12/01/1974NES3638
10/15/1972NES4862
12/01/1970NES5261
10/15/1968NES6660
12/01/1966NES7154
10/15/1964NES8073
12/01/1958NES7179
Date.Liberal Dem/Lean DemCons-Moderate Dem/Lean DemModerate-Lib Rep/Lean RepConservative Rep/Lean Rep
5/19/2024PEW3336177
6/11/2023PEW2327144
5/1/2022PEW2632137
4/11/2021PEW3140165
8/2/2020PEW8163127
4/12/2020PEW12223737
3/25/2019PEW13152120
12/04/2017PEW15162620
4/11/2017PEW15163226
10/04/2015PEW2825149
7/20/2014CNN1916157
2/26/2014PEW31332113
11/15/2013CBS/NYT3825135
10/13/2013PEW2527167
5/31/2013CBS/NYT3030164
2/06/2013CBS/NYT353497
1/13/2013PEW34371714
10/31/2012NES26321815
10/19/2011CBS/NYT913117
10/04/2011PEW3025149
9/23/2011CNN30161111
8/21/2011PEW26241810
3/01/2011PEW36333218
10/21/2010CBS/NYT3735124
10/01/2010CBS/NYT34221016
9/06/2010PEW39311910
9/01/2010CNN36302811
4/05/2010CBS/NYT3721237
3/21/2010PEW36311911
2/12/2010CNN3634259
2/05/2010CBS/NYT3132137
1/10/2010GALLUP29222012
12/20/2009CNN31231813
8/31/2009CBS/NYT38301410
6/12/2009CBS/NYT4234138
12/21/2008CNN36282817
10/15/2008NES37344828
10/13/2008CBS/NYT16122612
7/09/2007CBS/NYT14213828
1/09/2007PEW15254145
10/08/2006CBS/NYT14225051
9/15/2006CBS/NYT11234444
2/05/2006PEW13235254
1/20/2006CBS/NYT27215250
1/06/2006GALLUP10263356
12/02/2005CBS/NYT16216047
9/11/2005PEW13223954
9/09/2005CBS/NYT12264641
6/19/2005GALLUP25243141
10/15/2004NES24396359
3/21/2004PEW23245356
10/26/2003GALLUP23393152
7/27/2003CBS/NYT21275547
10/15/2002NES53566661
9/04/2002GALLUP31405060
9/02/2002CBS/NYT32325553
7/13/2002CBS/NYT37335042
6/17/2002GALLUP30365955
1/24/2002CBS/NYT38395854
12/07/2001CBS/NYT34436158
10/06/2001GALLUP46556669
1/17/2001CBS/NYT33244133
10/15/2000NES58525444
7/09/2000GALLUP41425035
4/02/2000ABC/POST38392820
10/03/1999CBS/NYT26332924
9/14/1999CBS/NYT38454227
2/12/1999ABC/POST40432616
2/04/1999GALLUP36403327
1/10/1999CBS/NYT39444028
1/03/1999CBS/NYT34393126
12/01/1998NES45463934
11/01/1998CBS/NYT28282322
10/26/1998CBS/NYT30282226
8/10/1998ABC/POST38352427
2/01/1998GALLUP55523323
1/25/1998CBS/NYT24312419
6/01/1997GALLUP41383121
1/14/1997CBS/NYT30282514
11/02/1996CBS/NYT30322119
10/15/1996NES38393025
5/12/1996GALLUP25352518
5/06/1996ABC/POST41413933
11/19/1995ABC/POST26272628
8/07/1995GALLUP16271725
8/05/1995CBS/NYT21191923
3/19/1995ABC/POST24282217
2/22/1995CBS/NYT20182217
12/01/1994NES22282116
10/29/1994CBS/NYT26272315
10/23/1994ABC/POST32252211
6/06/1994GALLUP1626159
1/30/1994GALLUP20271812
1/20/1994ABC/POST26312510
1/17/1993ABC/POST30332822
1/14/1993CBS/NYT17302020
10/23/1992CBS/NYT20153032
10/15/1992NES26333731
6/08/1992GALLUP13193130
10/20/1991ABC/POST25334239
3/06/1991CBS/NYT46395756
3/01/1991ABC/POST39415450
12/01/1990NES27263133
9/06/1990ABC/POST34394945
1/16/1990ABC/POST28345039
6/29/1989CBS/NYT27273855
1/15/1989CBS/NYT33385654
11/10/1988CBS/NYT24406552
10/15/1988NES34355251
1/23/1988ABC/POST30315449
10/18/1987CBS/NYT34374749
6/01/1987ABC/POST34416055
1/21/1987CBS/NYT34375448
1/19/1987ABC/POST37385251
12/01/1986NES25365353
9/09/1986ABC/POST25345544
1/19/1986CBS/NYT34385152
11/06/1985CBS/NYT42436056
7/29/1985ABC/POST26335341
3/21/1985ABC/POST27295248
2/22/1985ABC/POST28336263
10/15/1984NES34475246
12/01/1982NES29354838
11/07/1980CBS/NYT38424441
10/15/1980NES34282818
3/12/1980CBS/NYT31292518
11/03/1979CBS/NYT34312826
12/01/1978NES38332424
10/23/1977CBS/NYT41413216
4/25/1977CBS/NYT41383336
10/15/1976NES27344941
9/05/1976CBS/NYT33424545
6/15/1976CBS/NYT35353934
12/01/1974NES36403940
10/15/1972NES44536266

Among Asian, Hispanic and Black adults, 36%, 30% and 27% respectively say they trust the federal government “most of the time” or “just about always” – higher levels of trust than among White adults (19%).

During the last Democratic administration, Black and Hispanic adults similarly expressed more trust in government than White adults. Throughout most recent Republican administrations, White Americans were substantially more likely than Black Americans to express trust in the federal government to do the right thing.

Date.HispanicBlackWhiteAsian
5/19/2024PEW30271936
6/11/2023PEW23211323
5/1/2022PEW29241637
4/11/2021PEW36371829
8/2/2020PEW28151827
4/12/2020PEW292726
3/25/2019PEW28917
12/04/2017PEW231517
4/11/2017PEW241320
10/04/2015PEW282315
7/20/2014CNN9
2/26/2014PEW332622
11/15/2013CBS/NYT12
10/13/2013PEW212417
5/31/2013CBS/NYT15
2/06/2013CBS/NYT3915
1/13/2013PEW443820
10/31/2012NES383816
10/19/2011CBS/NYT15158
10/04/2011PEW292517
9/23/2011CNN10
8/21/2011PEW283515
3/01/2011PEW282530
10/21/2010CBS/NYT4015
10/01/2010CBS/NYT17
9/06/2010PEW373720
9/01/2010CNN21
4/05/2010CBS/NYT18
3/21/2010PEW263720
2/12/2010CNN22
2/05/2010CBS/NYT16
1/10/2010GALLUP16
12/20/2009CNN2118
8/31/2009CBS/NYT21
6/12/2009CBS/NYT16
12/21/2008CNN22
10/15/2008NES342830
10/13/2008CBS/NYT18
7/09/2007CBS/NYT1125
1/09/2007PEW352032
10/08/2006CBS/NYT31
9/15/2006CBS/NYT31
2/05/2006PEW2636
1/20/2006CBS/NYT1934
1/06/2006GALLUP33
12/02/2005CBS/NYT35
9/11/2005PEW1232
9/09/2005CBS/NYT1229
6/19/2005GALLUP32
10/15/2004NES3450
3/21/2004PEW1741
10/26/2003GALLUP39
7/27/2003CBS/NYT1937
10/15/2002NES4158
9/04/2002GALLUP46
9/02/2002CBS/NYT39
7/13/2002CBS/NYT39
6/17/2002GALLUP48
1/24/2002CBS/NYT48
12/07/2001CBS/NYT51
10/25/2001CBS/NYT60
10/06/2001GALLUP61
1/17/2001CBS/NYT33
10/15/2000NES3246
7/09/2000GALLUP41
4/02/2000ABC/POST28
2/14/2000PEW3640
10/03/1999CBS/NYT28
9/14/1999CBS/NYT3039
5/16/1999PEW2831
2/21/1999PEW3231
2/12/1999ABC/POST32
2/04/1999GALLUP33
1/10/1999CBS/NYT3735
1/03/1999CBS/NYT3931
12/01/1998NES573638
11/19/1998PEW2726
11/01/1998CBS/NYT2922
10/26/1998CBS/NYT2625
8/10/1998ABC/POST33
2/22/1998PEW4233
2/01/1998GALLUP36
1/25/1998CBS/NYT25
10/31/1997PEW3938
6/01/1997GALLUP3132
1/14/1997CBS/NYT1524
11/02/1996CBS/NYT313024
10/15/1996NES3532
5/12/1996GALLUP24
5/06/1996ABC/POST34
11/19/1995ABC/POST26
8/07/1995GALLUP22
8/05/1995CBS/NYT2419
3/19/1995ABC/POST2721
2/22/1995CBS/NYT2017
12/01/1994NES2220
10/29/1994CBS/NYT1622
10/23/1994ABC/POST21
6/06/1994GALLUP15
1/30/1994GALLUP17
1/20/1994ABC/POST3421
3/24/1993GALLUP20
1/17/1993ABC/POST4525
1/14/1993CBS/NYT2224
10/23/1992CBS/NYT2123
10/15/1992NES372728
6/08/1992GALLUP23
10/20/1991ABC/POST2936
3/06/1991CBS/NYT3049
3/01/1991ABC/POST3546
12/01/1990NES392227
10/28/1990CBS/NYT2625
9/06/1990ABC/POST3943
1/16/1990ABC/POST3538
6/29/1989CBS/NYT2636
1/15/1989CBS/NYT3346
11/10/1988CBS/NYT3345
10/15/1988NES2543
1/23/1988ABC/POST2941
10/18/1987CBS/NYT3241
6/01/1987ABC/POST3449
3/01/1987CBS/NYT2045
1/21/1987CBS/NYT2746
1/19/1987ABC/POST3147
12/01/1986NES2142
11/30/1986CBS/NYT2352
9/09/1986ABC/POST2642
1/19/1986CBS/NYT2245
11/06/1985CBS/NYT3452
7/29/1985ABC/POST2240
3/21/1985ABC/POST2940
2/22/1985ABC/POST2446
10/15/1984NES3346
12/01/1982NES2634
11/07/1980CBS/NYT3040
10/15/1980NES2625
3/12/1980CBS/NYT3524
11/03/1979CBS/NYT3629
12/01/1978NES2929
10/23/1977CBS/NYT2834
4/25/1977CBS/NYT3435
10/15/1976NES2235
6/15/1976CBS/NYT3534
3/01/1976GALLUP2334
12/01/1974NES1938
10/15/1972NES3256
12/01/1970NES4055
10/15/1968NES6261
12/01/1966NES6565
10/15/1964NES7777
12/01/1958NES6274

Note: For full question wording, refer to the topline . White, Black and Asian American adults include those who report being one race and are not Hispanic. Hispanics are of any race. Estimates for Asian adults are representative of English speakers only.

Sources: Pew Research Center, National Election Studies, Gallup, ABC/Washington Post, CBS/New York Times, and CNN Polls. Data from 2020 and later comes from Pew Research Center’s online American Trends Panel; prior data is from telephone surveys. Details about changes in survey mode can be found in this 2020 report . Read more about the Center’s polling methodology . For analysis by party and race/ethnicity, selected datasets were obtained from searches of the iPOLL Databank provided by the Roper Center for Public Opinion Research .

Sign up for our weekly newsletter

Fresh data delivered Saturday mornings

1615 L St. NW, Suite 800 Washington, DC 20036 USA (+1) 202-419-4300 | Main (+1) 202-857-8562 | Fax (+1) 202-419-4372 |  Media Inquiries

Research Topics

  • Email Newsletters

ABOUT PEW RESEARCH CENTER  Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of  The Pew Charitable Trusts .

© 2024 Pew Research Center

IMAGES

  1. 40+22 Information Technology Research Topics to Obtain PhD

    research topics on information science

  2. 110 Unique Data Science Topics to Consider for Academic Work

    research topics on information science

  3. 130 Excellent Science Research Paper Topics to Consider

    research topics on information science

  4. Computer Science Research Topics

    research topics on information science

  5. 230 Innovative Technology Research Topics To Deal With

    research topics on information science

  6. 99+ Interesting Data Science Research Topics For Students

    research topics on information science

VIDEO

  1. Introduction to Research and how to choose a research topic

  2. Introduction to Information Science

  3. Top 5 Most Important Topics To Study For CSIR NET Life Science

  4. Pulling ideas from the brain

  5. The possible impact of AI on search and discovery​

  6. What Is the Information Society and Why Does It Matter?

COMMENTS

  1. Library & Information Science Research

    Library & Information Science Research, a cross-disciplinary and refereed journal, focuses on the research process in library and information science, especially demonstrations of innovative methods and theoretical frameworks or unusual extensions or applications of well-known methods and tools. …. View full aims & scope $3520

  2. Research Topics & Ideas: Data Science

    If you're just starting out exploring data science-related topics for your dissertation, thesis or research project, you've come to the right place. In this post, we'll help kickstart your research by providing a hearty list of data science and analytics-related research ideas, including examples from recent studies.. PS - This is just the start…

  3. Emerging trends and new developments in information science ...

    Characterizing the structure of knowledge, the evolution of research topics, and the emergence of topics has always been an important part of information science (IS). Our previous scientometric review of IS provided a snapshot of this fast-growing field up to the end of 2008. This new study aims to identify emerging trends and new developments appearing in the subsequent 7574 articles ...

  4. Research Methods in Library and Information Science

    Library and information science (LIS) is a very broad discipline, which uses a wide rangeof constantly evolving research strategies and techniques. The aim of this chapter is to provide an updated view of research issues in library and information science. A stratified random sample of 440 articles published in five prominent journals was analyzed and classified to identify (i) research ...

  5. Research Areas

    FATE (fairness, accountability, transparency, ethics) Researching the complex social implications of AI, machine learning, data science, large-scale experimentation, and increasing automation; and developing computational techniques that draw on the deeper context surrounding these issues from sociology, history, and science and technology studies.

  6. Journal of Information Science: Sage Journals

    The Journal of Information Science is a peer-reviewed international journal of high repute covering topics of interest to all those researching and working in the sciences of information and knowledge management. The Editors welcome material on any aspect of information science theory, policy, application or practice that will advance thinking in the field.

  7. Information Sciences

    The journal publishes high-quality, refereed articles. It emphasizes a balanced coverage of both theory and practice. It fully acknowledges and vividly promotes a breadth of the discipline of Informations Sciences. Topics include: Information Theory, Mathematical Linguistics, Automata Theory, Cognitive Science, Theories of Qualitative Behaviour ...

  8. Information Research

    Conceptual orientation. Annemaree Lloyd, in Information Literacy Landscapes, 2010. Information practice research in library and information science. Although the concept of information practice, is still emerging in the library and information science field, it has gradually been made visible in information research by those who are interested finding an 'alternative to the dominant concept ...

  9. Journal of the Association for Information Science and Technology

    Employing approaches adopted from studies of library and information science (LIS) research trends performed by Järvelin et al., this content analysis systematically examines the evolution and distribution of LIS research topics and data collection methods at 6-year increments from 2006 to 2018.

  10. 114178 PDFs

    Information science (or information studies) is an interdisciplinary field primarily concerned with the analysis, collection, classification,... | Explore the latest full-text research PDFs ...

  11. Information science

    Information science is an academic field which is primarily concerned with analysis, collection, classification, manipulation, storage, retrieval, movement, dissemination, and protection of information. Practitioners within and outside the field study the application and the usage of knowledge in organizations in addition to the interaction between people, organizations, and any existing ...

  12. Library and Information Science research areas: A content analysis of

    Includes reports of basic and applied research in information science, computer science, cognitive science, deals also with: generation, representation, organization, storage, retrieval and use of information ... An international journal covering topics of interest to all those researching and working in the sciences of information and ...

  13. Global Research Trends and Hot Topics on Library and Information

    Therefore, this study aimed to determine the research trends on the Library and Information Science (LIS) in the Scopus database during 2011-2020 and specify the hot topics in this field from July ...

  14. Popular research topics in the recent journal publications of library

    Research topic studies have gained popularity in many disciplines, including library and information science (LIS). However, the lack of representation of library science and librarianship in ...

  15. Picking Research Topics in Library and Information Science

    A systematic approach is best when undertaking research in the library and information science. Not only should you have an in-depth knowledge of major themes in the area, but you should also be aware of current research methods and topics of influence, such as library systems, cooperation between libraries, and the flow of information between ...

  16. A bibliometric model for identifying emerging research topics

    Journal of the Association for Information Science and Technology is a leading international forum for peer-reviewed research in information science. Detecting emerging research topics is essential, not only for research agencies but also for individual researchers. Previous studies have created various bibliographic indicators for the identific...

  17. Top 400 Information Technology Research Topics

    The list of the top 400 information technology research topics is organized into different categories. Let's examine it. Artificial Intelligence (AI) and Machine Learning (ML) Easy AI: Explaining and Using. Group Learning: Getting Better Together. AI in Health: Diagnosing and Helping. Robots Learning on Their Own.

  18. Latest Trends In Library And Information Science

    As repositories and access points of information, libraries are often defined by their collections. Collection management is a major component of any Library and Information Science (LIS) degree program. In addition to books, newspapers, magazines, and audio-visual content, library resources in the 21st century are significantly enhanced by new ...

  19. Popular research topics in the recent journal publications of library

    Research topic studies have gained popularity in many disciplines, including library and information science (LIS). However, the lack of representation of library science and librarianship in literature indicates a research bias due to the preset methodology parameters, which are commonly based on impact factor scores in the Journal Citation Report of Thomson Reuters.

  20. 100 Science Topics for Research Papers

    Research Sources. Science: As a premier publication in the field, Science publishes peer-reviewed research and expert-curated information. Nature: Publishes peer-reviewed articles on biology, environment, health, and physical sciences. Nature is an authoritative source for current information. If articles are difficult to read, you can search ...

  21. Library and Information Science Research Papers/Topics

    1 - 15 Of 212 Results. Browse through books in Library and Information Science. Access and download complete Library and Information Science books, Library and Information Science text books, book reviews etc. Book reviews in Library and Information Science - Page 1.

  22. How to Vet Information Before Making a Decision

    Read more on Decision making and problem solving or related topics Organizational decision making, Market research, Information management, Analytics and data science and Leadership Partner Center

  23. 188 questions with answers in INFORMATION SCIENCE

    Information science (or information studies) is an interdisciplinary field primarily concerned with the analysis, collection, classification,... | Review and cite INFORMATION SCIENCE protocol ...

  24. These are the Top 10 Emerging Technologies of 2024

    With AI expanding the world of data like never before, finding ways of leveraging it without ethical or security concerns is key. Enter synthetic data, an exciting privacy-enhancing technology re-emerging in the age of AI. It replicates the patterns and trends in sensitive datasets but does not contain specific information that could be linked to individuals or compromise organizations or ...

  25. Science of social media's effect on mental health isn't as clear cut as

    Future research should focus on following trends over time - tracking the mental health of the same children before and after exposure to social media to see what effects it has - and digging ...

  26. Sharing false political information on social media may be associated

    More information: Individual differences in sharing false political information on social media: Deliberate and accidental sharing, motivations and positive schizotypy, PLoS ONE (2024). DOI: 10. ...

  27. Public Trust in Government: 1958-2024

    ABOUT PEW RESEARCH CENTER Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions.

  28. Science Topics

    About ScienceDirect Topics. Topic pages are designed to help you get up to speed with new topics in your field of research or area of study. The extracts provided on ScienceDirect Topics are written by subject matter experts and are drawn from foundational and reference materials. ScienceDirect makes use of machine learning (ML) and natural ...

  29. FDA Omics Days 2024

    At the FDA Omics Days 2024, the FDA Omics Working Group will be hosting speakers from industry, academia, and government to discuss topics important to the FDA. This event will include sessions on ...

  30. Layers of carbonate provide insight into the world of the ancient

    Archaeologists face a major challenge when they intend to acquire information about buildings or facilities of which only ruins remain. This was a particular challenge for the remnants of the ...