Discovery of factors influencing citation impact based on a soft fuzzy rough set model

Scientometrics

Volumn 93, Issue 3, 2012, Pages 635-644

  Wang, Mingyang ^a,b   Yu, Guang ^b   An, Shuang ^b   Yu, Daren ^b  

^a NORTHEAST FORESTRY UNIVERSITY   (China)

^b HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Citation impact; Highly cited papers; Soft fuzzy rough set

Indexed keywords

EID: 84869197600     PISSN: 01389130     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11192-012-0766-x     Document Type: Article

References (30)

1. Aksnes, D. W. (2003). Characteristics of highly cited papers. Research Evaluation, 12(3), 159-170.
2. Bornmann, L., & Daniel, H. D. (2008). What do citation counts measure? A review of studies on citing behavior. Journal of Documentation, 64(1), 45-80.
3. Burrell, Q. L. (2001). Stochastic modelling of the first-citation distribution. Scientometrics, 52, 3-12.
4. Burrell, Q. L. (2002a). On the nth-citation distribution and obsolescence. Scientometrics, 53, 309-323.
5. Burrell, Q. L. (2002b). Will this paper ever be cited? Journal of the American Society for Information Science and Technology, 53, 232-235.
6. Burrell, Q. L. (2003). Predicting future citation behavior. Journal of the American Society for Information Science and Technology, 54(5), 372-378.
7. Case, D. O., & Higgins, G. M. (2000). How can we investigate citation behavior? A study of reasons for citing literature in communication. Journal of the American Society for Information Science, 51(7), 635-645.
8. Cover, T. M., & Hart, P. E. (1967). Nearest neighbor pattern classification. IEEE Transaction on Information Theory, IT-13(1), 21-27.
9. Danell, R. (2011). Can the quality of scientific work be predicted using information on the author's track record? Journal of the American Society for Information Science and Technology, 62(1), 50-60.
10. Dubois, D., & Prade, H. (1990). Rough fuzzy sets and fuzzy rough sets. General Systems, 17, 191-209.
11. Fu, L., & Aliferis, C. (2010). Using content-based and bibliometric features for machine learning models to predict citation counts in the biomedical literature. Scientometrics, 85, 257-270.
12. Glänzel, W. (1997). On the reliability of predictions based on stochastic citation processes. Scientometrics, 40(3), 481-492.
13. Glänzel, W., Rinia, E. J., & Brocken, M. G. M. (1995). A bibliometric study of highly cited European physics papers in the 80s. Research Evaluation, 5(2), 113-122.
14. Glänzel, W., & Schubert, A. (1995). Predictive aspects of a stochastic model for citation processes. Information Processing and Management, 31(1), 69-80.
15. Glänzel, W., Schlemmer, B., & Thijs, B. (2003). Better late than never? On the chance to become highly cited only beyond the standard bibliometric time horizon. Scientometrics, 58(3), 571-586.
16. Hewings, A., Lillis, T., & Vladimirou, D. (2010). Who's citing whose writings? A corpus based study of citations as interpersonal resource in English medium national and English medium international journals. Journal of English for Academic Purposes, 9(2), 102-115.
17. Hirsch, J. E. (2005). An index to quantify an individual's scientific research output. Proceedings of the National Academy of Sciences of the USA, 102(46), 16569-16572.
18. Hu, Q. H., An, S., & Yu, D. R. (2010). Soft fuzzy rough sets for robust feature evaluation and selection. Information Sciences, 180, 4384-4400.
19. Kim, K. (2004). The motivation for citing specific references by social scientists in Korea: The phenomenon of co-existing references. Scientometrics, 59(1), 79-93.
20. Laband, D. N., & Piette, M. J. (1994). Favoritism versus search for good papers: Empirical evidence regarding the behavior of journal editors. Journal of Political Economy, 102, 194-203.
21. Levitt, J. M., & Thelwall, M. (2008). Is multidisciplinary research more highly cited? A macrolevel study. Journal of the American Society for Information Science and Technology, 59(12), 1973-1984.
22. Levitt, J. M., & Thelwall, M. (2009). The most highly cited Library and Information Science articles: Interdisciplinarity, first authors and citation patterns. Scientometrics, 78(1), 45-67.
23. Merton, R. K. (1968). The Matthew effect in science. Science, 159, 56-63.
24. Penas, C. S., & Willett, P. (2006). Gender differences in publication and citation counts in librarianship and information science research. Journal of Information Science, 32(5), 480-485.
25. Rong, T., & Martin, A. S. (2008). Author-rated importance of cited references in biology and psychology publications. Journal of Documentation, 64(2), 246-272.
26. Sagi, I., & Yechiam, E. (2008). Amusing titles in scientific journals and article citation. Journal of Information Science, 34(5), 680-687.
27. van Dalen, H. P., & Henkens, K. (2001). What makes a scientific article influential? The case of demographers. Scientometrics, 50, 455-482.
28. van Dalen, H. P., & Henkens, K. (2005). Signals in science-on the importance of signaling in gaining attention in science. Scientometrics, 64(2), 209-233.
29. Wang, M. Y., Yu, G., & Yu, D. R. (2011). Mining typical features for highly cited papers. Scientometrics, 87(3), 695-706.
30. Xia, J. F., Myers, R. L., & Wihoite, S. K. (2011). Multiple open access availability and citation impact. Journal of Information Science, 37(1), 19-28.