چکیده:
This research examines the association between co-authorship network centrality (degree, closeness, betweenness, eigenvector, Bonacich flow betweenness) and productivity of Information science researchers. The research population includes all those researchers who have published at least one record in one of the twenty journals of Information Science which has an impact factor of 0.635 as a minimum from the years 1996 to 2010. By using social network analyses, this study examines information science researchers’ outputs during 1996-2011 in ISI Web of Science database. In general co-authorship network of these researchers was analyzed by UCINET6 software. Results showed that there is a significant correlation between Journal Impact Factor (JIF) and all centrality measures except closeness centrality at P= 0.001. Results also showed that there is a significant correlation between productivity of authors and all centrality measures scores at P≥
0.001. Also, regression reports direct relationship of degree, closeness and flow betweenness and inverse relationship of betweenness as well as Eigen vector centrality on productivity of researchers.
خلاصه ماشینی:
Correlation between Impact Factor and productivity with centrality measures in journals of Information science: A social network analysis Faramarz Soheili Payame Noor University, Tehran, Iran Corresponding author: fsohie1iHgmai1.
com Rohallah Khademi Shahid Chamran University, Ahvaz, Iran Ali Mansoori Isfahan University, Isfahan, Iran Abstract This research examines the association between co-authorship network centrality (degree, closeness, betweenness, eigenvector, Bonacich flow betweenness) and productivity of Information science researchers.
Results also showed that there is a significant correlation between productivity of authors and all centrality measures scores at P Keywords: Co-authorship; Network centrality; Scientific productivity; Social analysis, Journal Impact Factor network Introduction The increasing cooperation in science, which has led to larger co-authorship networks, requires the application of new methods of analysis of social networks in bibliographic co- authorship networks as well as in networks visible on the Web (Kretschmer, 2004).
In this study, social network analysis has been used to gain a good perception of the node (namely, identifying authors with central role) in information science researchers.
Table 2 Correlations between centrality scores and Journal impact factor {مراجعه شود به فایل جدول الحاقی} Results about analysis of centrality measures of authors in all examined journals showed that “GLANZEL” in Scientometrics with degree centrality scores 94 ranked the first, “BATES” in Journal of the American Medical Informatics Association with degree centrality scores 70 and “HERNON” in Library & Information Science Research with degree centrality Scores 77 ranked the second and the third.