CiteULike bookmarks are correlated to citations at journal and author levels in library and information science
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Aiming to explore the applicability of bookmarking data in measuring the scientific impact, the present study investigates the correlation between conventional impact indicators (i.e. impact factors and mean citations) and bookmarking metrics (mean bookmarks and percentage of bookmarked articles) at author and journal aggregation levels in library and information science (LIS) field. Applying the citation analysis method, it studies a purposeful sample of LIS articles indexed in SSCI during 2004–2012 and bookmarked in CiteULike. Data are collected via WoS, Journal Citation Report, and CiteULike. There is a positive, though weak, correlation between LIS authors’ mean citations and their mean bookmarks, as well as a moderate to large correlation between LIS journals’ impact factors on the one hand and on the other, their mean bookmarks, and the percentage of their bookmarked articles. Given the correlation between the citation- and bookmark-based indicators at author and journal levels, bookmarking data can be used as a complement to, but not a substitute for, the traditional indicators to get to a more inclusive evaluation of journals and authors.
KeywordsAltmetrics Citations CiteULike Bookmarks Library and information science
- Bar-Ilan, J., Haustein, S., Peters, I., Priem, J., Shema, H., & Terliesner, J. (2012). Beyond citations: Scholars’ visibility on the social web. arXiv preprint arXiv:1205.5611.Google Scholar
- Costas, R., Zahedi, Z., & Wouters, P. (2014). Do altmetrics correlate with citations? Extensivecomparison of altmetric indicators with citations from a multidisciplinary perspective. Arxiv preprint arXiv: 1401.4321.Google Scholar
- Harnad, S. (2008).Validating research performance metrics against peer rankings. Ethics in Science and Environmental Politics, 8(11). Retrieved July 10, 2010, from http://eprints.ecs.soton.ac.uk/15619/1/esep-harnad.html.
- Haustein, S., Golov, E., Luckanus, K., Reher, S., & Terliesner, J. (2010). Journal evaluation and science 2.0.Using social bookmarks to analyze reader perception. “In book of abstracts of the 11 th International Conference on Science and Technology Indicators”, (pp. 117–119). Leiden, The Netherlands.Google Scholar
- Li, X., & Thelwall, M. (2012). F1000, Mendeley and traditional bibliometric indicators. In E. Archambault, Y. Gingras & V. Lariviere (Eds.), The 17 th International Conference on Science and Technology Indicators, (pp. 541–551). Montreal, Canada: Repro-UQAM.Google Scholar
- Maflahi, N. & Thelwall, M. (in press).When are readers as good as citers for bibliometrics? Scopus versus Mendeley for LIS journals. Journal of the Association for Information Science and Technology.Google Scholar
- Mohammadi, E., Thelwall, M., Haustein, S., & Larivière, V. (in press).Who reads research articles? An altmetrics analysis of Mendeley user categories. Journal of the Association for Information Science and Technology.Google Scholar
- Mohammadi, E., Thelwall, M., & Kousha, K. (in press). Can Mendeley bookmarks reflect readership? A survey of user motivations. Journal of the Association for Information Science and Technology.Google Scholar
- Ogden, T.L. & Bartley, D.L. (2008). “The ups and downs of journal impact factors.” Annals of Occupational Hygiene, 52(2):73–82. Retrieved July 10, 2010, from http://annhyg.oxfordjournals.org/cgi/reprint/52/2/73.
- Pallant, J. (2013). SPSS survival manual. UK: McGraw-Hill Education.Google Scholar
- Schlögl, C., Gorraiz, J., Gumpenberger, C., Jack, K., & Kraker, P. (2013). Download versus citation versus readership data: The case of an information systems journals. In Proceedings of the 14 th International Society of Scientometrics and Informetrics Conference, (pp. 626–634). Vienna, Austria.Google Scholar
- Sotudeh, H. (2010). A review of the journal impact factor and its deficiencies in research evaluation in different disciplines. Rahyaft, 47, 33–44. [in Persian].Google Scholar
- Sotudeh, H., Mazare’i, Z., & Mirza-beighi, M. (2015). The relationship between citation indicators and CiteULike bookmarks: The case of LIS field articles during 2004–2012. Information Processing and Management [in Persian], 30(4), 939–963.Google Scholar
- Taraborelli, D. (2008). Soft peer review: Social software and distributed scientific evaluation. In Proceedings of the eighth international conference on the design of cooperative systems (COOP ’08; Carry–Le–Rouet, 20–23 May). Available at http://nitens.org/docs/spr_coop08.pdf.
- Zahedi, Z., Fenner, M., & Costas, R. (2014). How consistent are altmetrics providers? Study of 1000 PLOS ONE publications using the PLOS ALM, Mendeley and Altmetric.com APIs. In altmetrics 14. Workshop at the Web Science Conference, Bloomington, USA.Google Scholar
- Zahedi, Z., & Van Eck, N.J. (2014). Visualizing readership activity of Mendeley users using VOSviewer. In altmetrics14: Expanding impacts and metrics, Workshop at Web Science Conference 2014, Bloomington, IN, doi: 10.6084/m9. figshare (Vol. 1041819).