A variant of the h-index to measure recent performance

Journal of the Association for Information Science and Technology

Volumn 66, Issue 11, 2015, Pages 2373-2380

  Schreiber, Michael ^a  

^a CHEMNITZ UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

quantitative research

Indexed keywords

H INDICES; HIRING PROCESS; PREDICTIVE POWER; QUANTITATIVE RESEARCH; RECENT PERFORMANCE; SCIENTIFIC ACHIEVEMENTS; WEB OF KNOWLEDGE;

INDEXING (OF INFORMATION);

EID: 84952314547     PISSN: 23301635     EISSN: 23301643     Source Type: Journal    
DOI: 10.1002/asi.23438     Document Type: Article

References (19)

1. Acuna, D.E., Allesina, S., &, Kording, K.P., (2012). Predicting scientific success. Nature, 489 (7415), 201-202.
2. Egghe, L., (2006). Theory and practice of the g-index. Scientometrics, 69 (1), 131-152.
3. Fiala, D., (2014). Current index: A proposal for a dynamic rating system for researchers. Journal of the Association for Information Science and Technology, 65 (4), 850-855.
4. García-Pérez, M.A., (2012). An extension of the h index that covers the tail and the top of the citation curve and allows ranking researchers with a similar h. Journal of Informetrics, 6 (4), 689-699.
5. García-Pérez, M.A., (2013). Limited validity of equations to predict the future h index. Scientometrics, 96 (3), 901-909.
6. García-Pérez, M.A., &, Núñez-Antõn, V., (2013). Correlation between variables subject to an order restriction, with application to scientometric indices. Journal of Informetrics, 7 (2), 542-554.
7. Hirsch, J.E., (2007). Does the h-index have predictive power? Proceedings of the National Academy of Sciences of the United States of America, 104 (49), 19193-19198.
8. Mazloumian, A., (2012). Predicting scholars' scientific impact. PLoS ONE, 7 (1 1), e49246.
9. Pan, R.K., &, Fortunato, S., (2014). Author impact factor: Tracking the dynamics of individual scientific impact. Scientific Reports, 4, 1-7.
10. Penner, O., Pan, R.K., Petersen, A.M., Kaski, K., &, Fortunato, S., (2013). On the predictability of future impact in science. Scientific Reports, 3, 1-8.
11. Penner, O., Petersen, A.M., Pan, R.K., &, Fortunato, S., (2013). The case for caution in predicting scientists' future impact. Physics Today, 66, 8-9.
12. Rousseau, R., (2006). Simple models and the corresponding h- and g-index. Retrieved from http://eprints.rclis.org/7501
13. Rousseau, R., &, Hu, X., (2012). Predicting the h-index. ISSI Newsletter, 8 (3), 53-55.
14. Schreiber, M., (2008). An empirical investigation of the g-index for 26 physicists in comparison with the h-index, the A-index, and the R-index. Journal of the American Society for Information Science and Technology, 59 (9), 1513-1522.
15. Schreiber, M., (2009). The influence of self-citation corrections and the fractionalised counting of multi-authored manuscripts on the Hirsch index. Annalen der Physik (Berlin), 18 (9), 607-621.
16. Schreiber, M., (2010). Revisiting the g-index: The average number of citations in the g-core. Journal of the American Society for Information Science and Technology, 61 (1), 169-174.
17. Schreiber, M., (2013a). How relevant is the predictive power of the h-index? A case study of the time-dependent Hirsch index. Journal of Informetrics, 7 (2), 325-329.
18. Schreiber, M., (2013b). The predictability of the Hirsch index evolution. In, S. Hinze, &, A. Lottmann, (Eds.), Translational twists and turns: Science as a socio-economic endeavor (pp. 366-372). Berlin: Institute for Research Information and Quality Assurance. Proc. STI 2013 Berlin, arXiv: 1307-5964.
19. Van Eck, N.J., &, Waltman, L., (2008). Generalizing the h- and g-indices. Journal of Informetrics, 2 (4), 263-271.