Journal of Information and Knowledge (Formerly SRELS Journal of Information Management)

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Misrepresentation of Citations: A Case Study of Google Scholar


Affiliations
1 Department of Library and Information Science, University of Kashmir, Srinagar – 190006, Jammu and Kashmir, India
     

   Subscribe/Renew Journal


The current study aims to identify the misrepresented and actual citations in Google Scholar and rank the professionals according to their correct accreditations. The selected Google Scholar profiles were analysed to reveal the misrepresentation of the citation counts based on the wrong indexing of author names. A total of 30 top prolific author profiles from Library and Information Science professionals were selected for this study. The publication and biographical data were gathered from Google Scholar and compared with Web of Science and Scopus to avoid ambiguity. The findings reveal that misrepresenting citations to the author profiles due to the wrong indexing of author names leads to an increased citation count and affects the resultant author ranking.

Keywords

Google Scholar, Misrepresented Citations, LIS Professionals, Scopus, Web of Science.
User
About The Authors

Nadim Akhtar Khan
Department of Library and Information Science, University of Kashmir, Srinagar – 190006, Jammu and Kashmir
India

Ajra Bhat
Department of Library and Information Science, University of Kashmir, Srinagar – 190006, Jammu and Kashmir
India


Notifications

  • Adesanya, A. A. (2023). The Nigerian Postgraduate Medical Journal: Award of impact factor of the web of science for the first time in the year 2023. Nigerian Postgraduate Medical Journal, 30(3), 181–182. https://doi.org/10.4103/npmj. npmj_172_23 PMid:37675693

  • Adriaanse, L. S., and Rensleigh, C. (2013). Web of Science, Scopus and Google Scholar: A content comprehensiveness comparison. The Electronic Library, 31(6), 727–744. https://doi.org/10.1108/EL-12-2011-0174

  • Anker, M. S., Hadzibegovic, S., Lena, A., and Haverkamp, W. (2019). The difference in referencing in Web of Science, Scopus, and Google Scholar. ESC Heart Failure, 6(6), 1291– 1312. https://doi.org/10.1002/ehf2.12583 PMid:31886636 PMCid:PMC6989289

  • Bilge, A., Shugerman, R. P., and Robertson, W. O. (1998). Misrepresentation of authorship by applicants to pediatrics training programs. Academic Medicine: Journal of the Association of American Medical Colleges, 73(5), 532– 533. https://doi.org/10.1097/00001888-199805000-00022 PMid:9609867

  • Chu, J. S., & Evans, J. A. (2021). Slowed canonical progress in large fields of science. Proceedings of the National Academy of Sciences, 118(41), Article e2021636118. https://doi.org/10.1073/pnas.2021636118 PMid:34607941 PMCid:PMC8522281

  • Clarivate (2023). Web of Science platform. Available at: https:// clarivate.com/products/scientific-and-academic-research/ research-discovery-and-workflow-solutions/webofscienceplatform/# benefits

  • Dogan, G., and Al, U. (2019). Is it possible to rank universities using fewer indicators? A study on five international university rankings. Aslib Journal of Information Management, 71(1), 18–37. https://doi.org/10.1108/AJIM- 05-2018-0118

  • Elsevier (2023). Welcome to Scopus preview. Available at: https://www.scopus.com/home.uri

  • Ferguson, C. J., Brown, J. M., and Torres, A. V. (2018). Education or indoctrination? The accuracy of introductory psychology textbooks in covering controversial topics and urban legends about psychology. Current Psychology, 37, 574–582. https:// doi.org/10.1007/s12144-016-9539-7

  • Fourie, I., and Bakker, S. (2013). Value of a manageable research life cycle for LIS: A cancer library exploring the needs of clinicians and researchers as example. The Electronic Library, 31(5), 648–663. https://doi.org/10.1108/EL-04- 2012-0034

  • Garfield, E., and Welljams-Dorof, A. (1992). Citation data: Their use as quantitative indicators for science and technology evaluation and policy-making. Science and Public Policy, 19(5), 321–327. https://doi.org/10.1093/spp/19.5.321

  • Goe, L. C., Herrera, A. M., and Mower, W. R. (1998). Misrepresentation of research citations among medical school faculty applicants. Academic Medicine: Journal of the Association of American Medical Colleges, 73(11), 1183–1186. https://doi.org/10.1097/00001888-199811000- 00017 PMid:9834702

  • Gurudevan, S. V., & Mower, W. R. (1996). Misrepresentation of research publications among emergency medicine residency applicantsGurudevan & Mower. Annals of Emergency Medicine, 27(3), 327–330. https://doi.org/10.1016/S0196- 0644(96)70268-8

  • Han, H., Zha, H., and Giles, C. L. (2005). Name disambiguation in author citations using a k-way spectral clustering method. Proceedings of the 5th ACM/IEEE-CS Joint Conference on Digital Libraries. https://doi.org/10.1145/1065385.1065462

  • Harzing, A. W. K., and van der Wal, R. (2008). Google Scholar as a new source for citation analysis. Ethics in Science and Environmental Politics, 8(1), 61–73. https:// doi.org/10.3354/esep00076

  • Harzing, A. W., and Alakangas, S. (2016). Google Scholar, Scopus and the Web of Science: A longitudinal and crossdisciplinary comparison. Scientometrics, 106, 787–804. https://doi.org/10.1007/s11192-015-1798-9

  • Kostoff, R. (1998). The use and misuse of citation analysis in research evaluation. Scientometrics, 43(1), 27–43. https:// doi.org/10.1007/bf02458392

  • Kulkarni, A. V., Aziz, B., Shams, I., and Busse, J. W. (2009). Comparisons of citations in Web of Science, Scopus, and Google Scholar for articles published in general medical journals. Jama, 302(10), 1092–1096. https://doi.org/10.1001/ jama.2009.1307 PMid:19738094

  • Lee, D., Kang, J., Mitra, P., Giles, C. L., and On, B. W. (2007). Are your citations clean? Communications of the ACM, 50(12), 33–38. https://doi.org/10.1145/1323688.1323690

  • Levine‐Clark, M., and Gil, E. (2009). A comparative analysis of social sciences citation tools. Online Information Review, 33(5), 986–996.https://doi.org/10.1108/14684520911001954

  • Li, J., Burnham, J. F., Lemley, T., and Britton, R. M. (2010). Citation analysis: Comparison of web of science®, scopus™, SciFinder®, and Google Scholar. Journal of Electronic Resources in Medical Libraries, 7(3), 196–217. https://doi. org/10.1080/15424065.2010.505518

  • Martin-Martin, A., Orduna-Malea, E., Thelwall, M., and López- Cózar, E. D. (2018). Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories. Journal of Informetrics, 12(4), 1160–1177. https://doi.org/10.1016/j.joi.2018.09.002

  • Meho, L. I., and Yang, K. (2006). A new era in citation and bibliometric analyses: Web of Science, Scopus, and Google Scholar. arXiv Preprint cs/0612132. Available at: https:// arxiv.org/abs/cs/0612132

  • Mingers, J., and Lipitakis, E. (2010). Counting the citations: A comparison of Web of Science and Google Scholar in the field of business and management. Scientometrics, 85(2), 613–625. https://doi.org/10.1007/s11192-010-0270-0

  • Mohammed, S., Morgan, A., and Nyantakyi, E. (2020). On the influence of uncited publications on a researcher’sh-index. Scientometrics, 122(3), 1791–1799.https://doi.org/10.1007/ s11192-020-03356-1

  • Nightingale, J. M., and Marshall, G. (2013). Reprint of Citation analysis as a measure of article quality, journal influence and individual researcher performance. Nurse Education in Practice, 13(5), 429–436. https://doi.org/10.1016/j. nepr.2013.02.005 PMid:23566748

  • O’Leary, D. (2008). On the relationship between citations and appearances on “top 25” download lists in the International Journal of Accounting Information Systems. International Journal of Accounting Information Systems, 9(1), 61–75. https://doi.org/10.1016/j.accinf.2008.02.001

  • Paice, E. (2001). How to write a peer review. Hospital Medicine, 62(3), 172–175. https://doi.org/10.12968/ hosp.2001.62.3.2392 PMid:11291469

  • Pavlovic, V., Weissgerber, T., Stanisavljevic, D., Pekmezovic, T., Milicevic, O., Lazovic, J. M., Cirkovic, A., Savic, M., Rajovic, N., Piperac, P., Djuric, N., Madzarevic, P., Dimitrijevic, A., Randjelovic, S., Nestorovic, E., Akinyombo, R., Pavlovic, A., Ghamrawi, R., Garovic, V., Milic, N. (2021). How accurate are citations of frequently cited papers in biomedical literature? Clinical Science, 135(5), 671–681. https://doi.org/10.1042/CS20201573 PMid:33599711 PMCid:PMC8048031

  • Prins, A. A., Costas, R., van Leeuwen, T. N., and Wouters, P. F. (2016). Using Google Scholar in research evaluation of humanities and social science programs: A comparison with Web of Science data. Research Evaluation, 25(3), 264– 270. https://doi.org/10.1093/reseval/rvv049

  • Sater, L., Schwartz, J. S., Coupland, S., Young, M., and Nguyen, L. H. (2015). Nationwide study of publication misrepresentation in applicants to residency. Medical Education, 49(6), 601–611. https://doi.org/10.1111/ medu.12729 PMid:25989408

  • Schroeder, R. (2007). Pointing users toward citation searching: Using Google Scholar and Web of Science. Libraries and the Academy, 7(2), 243–248. https://doi.org/10.1353/ pla.2007.0022

  • Strotmann, A., and Zhao, D. (2012). Author name disambiguation: What difference does it make in authorbased citation analysis? Journal of the American Society for Information Science and Technology, 63(9), 1820–1833. https://doi.org/10.1002/asi.22695

  • Tahamtan, I., and Bornmann, L. (2019). What do citation counts measure? An updated review of studies on citations in scientific documents published between 2006 and 2018. Scientometrics, 121, 1635–1684. https://doi.org/10.1007/ s11192-019-03243-4

  • Teixeira, M. C., Thomaz, S. M., Michelan, T. S., Mormul, R. P., Meurer, T., Fasolli, J. V. B., and Silveira, M. J. (2013). Incorrect citations give unfair credit to review authors in ecology journals. PLoS One, 8(12), Article e81871. https://doi.org/10.1371/journal.pone.0081871 PMid:24349143 PMCid:PMC3859513 PMid:24349143 PMCid:PMC3859513

  • Tokmachev, A. M. (2023). Hidden scales in statistics of citation indicators. Journal of Informetrics, 17(1), Article 101356. https://doi.org/10.1016/j.joi.2022.101356

  • Zhang, Y., Hu, L., Liao, S., Wang, Y., Ji, X., Liu, X., Huang, F., and Zhu, J. (2023). Bibliometric analysis of publications on enthesitis in spondyloarthritis in 2012–2021 based on web of science core collection databases. Rheumatology International, 43(1), 173–182. https://doi.org/10.1007/ s00296-022-05227-9 PMid:36464747


Abstract Views: 61

PDF Views: 4




  • Misrepresentation of Citations: A Case Study of Google Scholar

Abstract Views: 61  |  PDF Views: 4

Authors

Nadim Akhtar Khan
Department of Library and Information Science, University of Kashmir, Srinagar – 190006, Jammu and Kashmir, India
Ajra Bhat
Department of Library and Information Science, University of Kashmir, Srinagar – 190006, Jammu and Kashmir, India

Abstract


The current study aims to identify the misrepresented and actual citations in Google Scholar and rank the professionals according to their correct accreditations. The selected Google Scholar profiles were analysed to reveal the misrepresentation of the citation counts based on the wrong indexing of author names. A total of 30 top prolific author profiles from Library and Information Science professionals were selected for this study. The publication and biographical data were gathered from Google Scholar and compared with Web of Science and Scopus to avoid ambiguity. The findings reveal that misrepresenting citations to the author profiles due to the wrong indexing of author names leads to an increased citation count and affects the resultant author ranking.

Keywords


Google Scholar, Misrepresented Citations, LIS Professionals, Scopus, Web of Science.

References





DOI: https://doi.org/10.17821/srels%2F2023%2Fv60i6%2F170821