Altmetrics a 21 st-century solution to determining research quality

Online

Volumn 37, Issue 4, 2013, Pages 10-15

  Konkiel, Stacy ^a  

^a INDIANA UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84884361245     PISSN: 01465422     EISSN: None     Source Type: Trade Journal    
DOI: None     Document Type: Review

References (13)

1. Bar-Ilan, J., Haustein, S., Peters, I., Priem, J., Shema, H., & Terliesner, J. (2012). Beyond citations Scholars' visibility on the social web. Accepted to 17th International Conference on Science and Technology Indicators, Montreal, Canada, 5-8 Sept. 2012. (p. 14). Digital Libraries; Physics and Society, Montreal. Retrieved from arxiv.orgabs1205.5611.
2. Davis, P. M., & Solla, L. R. (2003). An IP-level analysis of usage statistics for electronic journals in chemistry Making inferences about user behavior. Journal of the American Society for Information Science and Technology, 54(11), 1062-1068. doi10.1002asi.10302.
3. Evans, P., & Krauthammer, M. (2011). Exploring the use of social media to measure journal article impact. AMIA ... Annual Symposium ProceedingsAMIA Symposium. AMIA Symposium, 2011, 374-81. Retrieved from pubmedcentral.nih.govarticlerender.fcgiartid=3243242&tool=pmcentrez &rendertype=abstract.
4. 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). Retrieved from jmir.org20114e123.
5. Haustein, S., & Siebenlist, T. (2011). Applying social bookmarking data to evaluate journal usage. Journal of Informetrics, 5(3), 457-446. Retrieved from dx.doi.org10.1016j.joi.2011 .04.002.
6. Hernández-Borges, A. A., Macías-Cervi, P., Gaspar-Guardado, M. A., Torres-Alvarez de Arcaya, M. L., Ruiz-Rabaza, A., & Jiménez-Sosa, A. (1999). Can examination of WWW usage statistics and other indirect quality indicators distinguish the relative quality of medical web sites Journal of Medical Internet Research, 1(1), E1. doi10.2196jmir.1.1.e1.
7. Li, X., & Thelwall, M. (2012). F1000, Mendeley and Traditional Bibliometric Indicators. 17th International Conference on Science and Technology Indicators (Vol. 3, pp. 1-11).
8. Li, X., Thelwall, M., & Giustini, D. (2011). Validating online reference managers for scholarly impact measurement. Scientometrics, 91(2), 1-11. doi10.1007s11192-011-0580-x.
9. Nielsen, F. (2007). Scientific citations in Wikipedia. First Monday, 12(8). Retrieved from arxiv.orgpdf0705.2106.
10. Priem, J., Piwowar, H. A., & Hemminger, B. M. (2012). Altmetrics in the wild Using social media to explore scholarly impact. ArXiv.org. Retrieved from arxiv.orgabs1203.4745.
11. Shema, H., Bar-Ilan, J., & Thelwall, M. (2012). Research blogs and the discussion of scholarly information. (C. A. Ouzounis, Ed.) PLoS ONE, 7(5), e35869. doi10.1371journal.pone.0035869.
12. Thelwall, M., Haustein, S., Larivière, V., & Sugimoto, C. R. (Preprint). Do altmetrics work Twitter and ten other social web. PLOS ONE. Retrieved from scit.wlv.ac.ukw~cm1993papersAltmetrics- preprintx.pdf.
13. Wolfe-Simon, F., Switzer Blum, J., Kulp, T. R., Gordon, G. W., Hoeft, S. E., Pett-Ridge, J., Stolz, J. F., Webb, P. K., Davies, P. C. W., Anbar, A. D., and Oremland, R. S. (2011). A bacterium that can grow by using arsenic instead of phosphorus. Science, 332(6034), pp. 1163-1166. doi10 .1126science.1197258.