Document Type : Articles
1 Saeideh Ebrahimi Assistant Prof. Knowledge and Information Science , Department of Knowledge and Information Science, College of Education and Psychology, Shiraz University, Iran,
2 M.A. in Knowledge and Information Science, Department of Knowledge and Information Science, College of Education and Psychology,
A review on previous literature shows that there is a correlation between discussion and recommendation. Therefore, we aimed to assess the relationship between these two metrics in four systems (Scopus, Web of Science, PubMed Central, and CrossRef) simultaneously and separately. This was a descriptive correlational study on 90728 research articles published in seven biomedical journals in the PLOS system during 2009-2013. The sample size was calculated based on the Cochrane formula to be 1892 articles. For data collection, PLOS system was used which enables free access to the articles of important biomedical journals. This system includes 7 journals cited from 2003. Data were analyzed usingSPSSsoftware, version21. Inthis study, we found a negative and statistically significant correlation between discussion on Twitter and the citation-based systems. We found no correlation between discussion on Facebook and citation. On the other hand, we found a positive and statistically significant correlation between recommendation by F1000 and citation. We found that discussion on virtual networks and recommendation are two types of feedback in virtual environments. However, among the various systems, the F1000 and Wikipedia were able to provide significant feedback leading to citation.
- Allen, L., Jones, C., Dolby, K., Lynn, D., & Walport, M. (2009). Looking for landmarks: The role of expert review and bibliometric analysis in evaluating scientific publication outputs. PLoS ONE, 4(6), e5910.
- Bornmann, L., & Haunschild, R. (2015). Which people use which scientific papers? An evaluation of data from F1000 and Mendeley. Journal of Informetrics, 9(3), 477-487.
- Bornmann, L., & Leydesdorff, L. (2013). The validation of (advanced) bibliometric indicators through peer assessments: a comparative study using data from InCItes and f1000. Informetrics, 7(2), 286–291.
- Butler, D. (2011). Experts question rankings of journals. Nature News, 478(7367), 20-20
- Click, A., & Petit, J. (2010). Social networking and web 2.0 in information literacy. The International Information & Library Review, 42, 137-142.
- Costas, R, Zahedi, Z., & Wouters, P. (2014). Do altmetics correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective. Journal of the Association for Information Science and Technology. Retrieved 2013, Dec. 15, from http://arxiv.org
- Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites. Journal of Computer‐Mediated Communication, 12(4), 1143-1168.
- Eysenbach, G. (2006). Citation advantage of open access articles. PLoS Biology, 4(5), 692.
- 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).
- Holmberg, K., & Thelwall, M. (2014). Disciplinary differences in Twitter scholarly communication. Scientometrics, 101(2), 1027-1042.
- Konkiel, S. (2013). Altmetrics: A 21st-century solution to determining research quality. Online Searcher, 37(4), 10-15.
- Konkiel, S., & Scherer, D. (2013). New opportunities for repositories in the age of altmetrics. Bulletin of the American Society for Information Science and Technology, 39(4), 22-26
- Kumar Das, A., & Mishra, S. (2014). Genesis of Altmetrics or article-level metrics for measuring efficacy of scholarly communications: current perspectives. Scientometric Research, 3 (2).
- Liu, J., & Adie, E. (2013). Five challenges in altmetrics: A toolmaker's perspective. Bulletin of the American Society for Information Science and Technology, 39(4), 31-34.
- Madge, C., Meek, J., Wellens, J., & Hooley, T. (2009). Facebook, social integration and informal learning at university:‘It is more for socialising and talking to friends about work than for actually doing work’. Learning, Media and Technology, 34(2), 141-155.
- Mohammadi, E., & Thelwall, M. (2013). Assessing non-standard article impact using f1000 labels. Scientometrics, 97 (2), 383-395.
- Mazov, N. A., & Gureev, V. N. (2015). Alternative approaches to assessing scientific results. Herald of the Russian Academy of Sciences, 85(1), 26-32.
- Parker, K., & Chao, J. (2007). Wiki as a teaching tool. Interdisciplinary Journal of E-learning and Learning Objects, 3(1), 57-72.
- Piwowar, H. (2013). Introduction Altmetrics: what, why and where? Bulletin of the Association for Information Science and Technology, 39 (4), 8-10.
- Scardilli, B. (2014). An introduction to Altmetrics. Information Today, 31 (9), 11-13.
- Shema, H., Bar-Ilan, J., & Thelwall, M. (2014). Do blog citations correlate with a higher number of future citations? Research blogs as a potential source for alternative metrics. Journal of the Association for Information Science and Technology, 65(5), 1018–1027.
- Shuai, X., Pepe, A., & Bollen, J. (2012). How the scientific community reacts to newly submitted preprints: Article downloads, twitter mentions, and citations. PLoS ONE, 7(11).
- Sud, P., & Thelwall, M. (2014). Evaluating altmetrics. Scientometrics, 98(2), 1131-1143.
- Thelwall, M., Haustein, S., Lariviere, V., & Sugimoto, C. (2013). Do altmetrics work? Twitter and ten other candidates. PLOS ONE, 8(5).
- Torres-Salinas, D., Cabezas-Clavijo, Á., & Jimenez-Contreras, E. (2013). Altmetrics: New indicators for scientific communication in web 2.0. ArXiv Preprint ArXiv: 1306.6595, Comunicar.
- Wardle, D. (2010). Do Faculty of 1000 (F1000) ratings of ecological publications serve as reasonable predictors of their future impact?. Ideas in Ecologyand Evolution. 3, 11-15.
- Weller, K. (2015). Social media and altmetrics: an overview of current alternative approaches to measuring scholarly impact. Incentives and Performance (pp. 261-276). Springer International Publishing AG.