How Network Characteristics of Researchers Relate to Their Citation Indicators – A Co-Authorship Network Analysis Based on Google Scholar
21 Pages Posted: 2 Oct 2017 Last revised: 5 Oct 2017
Date Written: September 29, 2017
The most common quantitative estimates of scientific performance are based on citation indices, and it is meaningful to identify what affects these indicators. In this work, we analyze the correlations between the citation characteristics of researchers and their co-authorship network parameters, which indicate the position of scientists in an academic network. To surpass the shortcoming of previous works we use a large sample and separate researchers by the year of their first citation. For constructing a co-authorship network, we used data about researchers from different disciplines, who have profiles in Google Scholar. The results of a count data regression model indicate that citations positively correlate with the number of co-authors, with position of the researcher in the co-authorship network (closeness centrality), and with the average number of co-author' citation. Also we reveal that the h-index and the i10-index are significantly associated with the number of co-authors and the average number of co-author citations. Based on these results, we can conclude that researchers who maintain more contacts and are more active than others have better bibliometric indicators on the average.
Keywords: co-authorship network; bibliometric analysis; Google Scholar; count data models
JEL Classification: A140; D830; Z130
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