A Bibliometric Analysis: A Tutorial for the Bibliometrix Package in R Using IRT Literature

Abstract

The bibliometrix package in R programming language, which is frequently used in bibliometric analysis, was introduced in this research. The article aimed to illustrate the various analyses applied in a bibliometric study. For this purpose, articles containing the "item response theory" (IRT) or "item response modeling" or "item response model" terms in the abstract were searched in the Thomson Reuters Clarivate Analytics Web of Science (WoS at http://www.webofknowledge.com), and bibliometric data was downloaded. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) steps were followed in the study. Data from 3388 IRT-related articles on education and psychology, searched between 2001 and 2021, were used in the study. Data were analyzed with the bibliometrix package. Some of the stages in data analysis were shared with screenshots. As a result of data analysis through the real data set, the author’s keywords related to IRT were item response model, differential item functioning, psychometrics, assessment, measurement, reliability, validity, Rasch model, and measurement invariance. The countries with the highest number of citations in IRT studies were the USA, Canada, Netherlands, United Kingdom, and China, respectively. Turkey ranked 12th in IRT studies with 434 citations. It was thought that bibliometric analysis of articles related to IRT would shed light on researchers in the field of psychometrics.

Keywords

• bibliometric analysis
• item response theory (IRT)
• biblioshiny
• bibliometrix
• R

References

1. Aksu, G., & Güzeller, C. O. (2019). Analysis of scientific studies on item response theory by bibliometric analysis method. International Journal of Progressive Education, 15(2), 44-64. https://doi.org/10.29329/ijpe.2019.189.4
2. Andrés, A. (2009). Measuring academic research: How to undertake a bibliometric study. Elsevier.
3. Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
4. Bailón-Moreno, R., Jurado-Alameda, E., Ruiz-Baños, R., & Courtial, J. P. (2005). Analysis of the field of physical chemistry of surfactants with the Unified Scienctometric Model. Fit of relational and activity indicators. Scientometrics, 63(2), 259-276. https://doi.org/10.1007/s11192-005-0212-4
5. Bock, R. D. (1997). A brief history of item response theory. Educational Measurement: Issues and Practice, 16, 21-33. https://doi.org/10.1111/j.1745-3992.1997.tb00605.x
6. Chen, C. (2006). CiteSpaceII: 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. https://doi.org/10.1002/asi.20317
7. Cobo, M. J., López‐Herrera, A. G., Herrera‐Viedma, E., & Herrera, F. (2012). SciMAT: A new science mapping analysis software tool. Journal of the American Society for Information Science and Technology, 63(8), 1609-1630. https://doi.org/10.1002/asi.22688
8. Demir, S. B. (2018). Predatory journals: Who publishes in them and why? Journal of Informetrics, 12(4), 1296-1311. https://doi.org/10.1016/j.joi.2018.10.008

9. Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W.M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285-296. https://doi.org/10.1016/j.jbusres.2021.04.070
10. Durieux, V., & Gevenois, P. A. (2010). Bibliometric indicators: Quality measurements of scientific publication. Radiology, 255(2), 342-351. https://doi.org/10.1148/radiol.09090626
11. Egghe, L. (2005). Expansion of the field of informetrics: Origins and consequences. Information Processing and Management, 41(6), 1311–1316. https://doi.org/10.1016/j.ipm.2005.03.011
12. Embretson, S. E., & Reise, S. P. (2013). Item response theory for psychologists. Lawrence Erlbaum.
13. Eysenck, H. J. (1973). The measurement of intelligence. Medical & Technical Publishing Co.
14. Garfield, E. (1955). Citation indexes for science. Science, 122(3159), 108-111. https://doi.org/10.1126/science.122.3159.108
15. Garfield, E. (1964). "Science Citation Index"-a new dimension in indexing. Science, 144(3619), 649-654. https://doi.org/10.1126/science.144.3619.649
16. Gómez Benito, J., Hidalgo Montesinos, M. D., Guilera Ferré, G., & Moreno Torrente, M. (2005). A bibliometric study of differential item functioning. Scientometrics, 64(1), 3-16. https://doi.org/10.1007/s11192-005-0234-y
17. Grauwin, S., & Sperano, I. (2018). Bibliomaps‐a software to create web‐based interactive maps of science: The case of UX map. Proceedings of the Association for Information Science and Technology, 55(1), 815-816. https://doi.org/10.1002/pra2.2018.14505501129
18. Gülmez, D., Özteke, İ., & Gümüş, S. (2020). Overview of educational research from turkey published in international journals: A bibliometric analysis. Education & Science, 46(206), 213-239. http://dx.doi.org/10.15390/EB.2020.9317
19. Gümüş, S., Bellibaş, M. Ş., Gümüş, E., & Hallinger, P. (2019). Science mapping research on educational leadership and management in Turkey: A bibliometric review of international publications. School Leadership & Management, 40(1), 1-22. https://doi.org/10.1080/13632434.2019.1578737
20. Hallinger, P., & Hammad, W. (2019). Knowledge production on educational leadership and management in Arab societies: A systematic review of research. Educational Management Administration & Leadership, 47(1), 20-36. https://doi.org/10.1177/1741143217717280
21. Hambleton, R. K., Swaminathan, H., & Rogers, H. J. (1991). Fundamentals of item response theory. Sage.
22. Linnenluecke, M. K., Marrone, M., & Singh, A. K. (2020). Conducting systematic literature reviews and bibliometric analyses. Australian Journal of Management, 45(2), 175-194. https://doi.org/10.1177/0312896219877678
23. Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & Prisma Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Mingerne, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097
24. National Center for Education Statistics (NCES). (2020). Number of degree-granting postsecondary institutions and enrollment in these institutions, by enrollment size, control, and classification of institution: Fall 2020. https://nces.ed.gov/programs/digest/d21/tables/dt21_317.40.asp
25. National Science Foundation (NSF). (2007). Asia’s rising science and technology strength: Comparative indicators for Asia, the European Union, and the United States. http://www.nsf.gov/statistics/nsf07319/pdf/nsf07319.pdf
26. Osareh, F. (1996). Bibliometrics, citation analysis and co-citation analysis: A review of literature I. Libri, 46(3), 149-158. https://doi.org/10.1515/libr.1996.46.3.149
27. Persson, O., Danell, R., & Schneider, J. W. (2009). How to use Bibexcel for various types of bibliometric analysis. Celebrating scholarly communication studies: A Festschrift for Olle Persson at his 60th Birthday, 5, 9-24. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-25636
28. Pritchard, A. (1969). Statistical bibliography or bibliometrics. Journal of Documentation, 25(4), 348-349. https://doi.org/10.1108/eb026482
29. R Core Team. (2021). R: A language and environment for statistical computing [Computer software]. R Foundation for Statistical Computing.
30. Rey-Rocha, J., Martín-Sempere, M., & Garzon, B. (2002). Research productivity of scientists in consolidated vs. non-consolidated teams: The case of Spanish university geologists. Scientometrics, 55(1), 137-156. https://doi.org/10.1023/a:1016059222182
31. Sci2Team. (2009). Science of Science (Sci2) Tool. Indiana University and SciTech Strategies. http://sci.slis.indiana.edu
32. Sengupta, I. N. (1992). Bibliometrics, informetrics, scientometrics and librametrics: An overview. Libri, 42,75–98. https://doi.org/10.1515/libr.1992.42.2.75
33. van Eck, N. J., & Waltman, L. (2014). CitNetExplorer: A new software tool for analyzing and visualizing citation networks. Journal of Informetrics, 8(4), 802-823. https://doi.org/10.1016/j.joi.2014.07.006
34. van Eck, N. J., & Waltman, L. (2010). Software survey: VoSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3
35. van Raan, A. F. (2004). Measuring science. In H. F. Moed, W. Glänzel & U. Schmoch (Eds.), Handbook of quantitative science and technology research (pp. 19-50). Wolters Kluwer. Springer.
36. Venables, W. N., Smith, D. M., & R Development Core Team. (2021). An introduction to R. https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf
37. Ware M., & Mabe, M. (2015). The STM report. An overview of scientific and scholarly journal publishing. The Hague: International Association of Scientific, Technical and Medical Publishers. https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1008&context=scholcom
38. Yurtçu, M., & Güzeller, C. (2021). Bibliometric analysis of articles on computerized adaptive testing. Participatory Educational Research, 8(4), 426-438. https://doi.org/10.17275/per.21.98.8.4
39. Zupic, I., & Cater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429-472. https://doi.org/10.1177/1094428114562629