How Network Characteristics of Researchers Relate to Their Citation Indicators – a Co-Authorship Network Analysis Based on Google Scholar

Nataliya Matveeva () and Oleg Poldin
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Nataliya Matveeva: National Research University Higher School of Economics

HSE Working papers from National Research University Higher School of Economics

Abstract: 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 (search for similar items in EconPapers)
JEL-codes: A14 D83 Z13 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2017
New Economics Papers: this item is included in nep-cta and nep-sog
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Published in WP BRP Series: Education / EDU, September 2017, pages 1-21

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Persistent link: https://EconPapers.repec.org/RePEc:hig:wpaper:44edu2017

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