 Influence of co-authorship networks in the research impact: Ego network analyses from Microsoft Academic SearchJosé Luis Ortega Journal of Informetrics, 2014, vol. 8, issue 3, 728-737 Abstract: The main objective of this study is to analyze the relationship between research impact and the structural properties of co-author networks. A new bibliographic source, Microsoft Academic Search, is introduced to test its suitability for bibliometric analyses. Citation counts and 500 one-step ego networks were extracted from this engine. Results show that tiny and sparse networks – characterized by a high Betweenness centrality and a high Average path length – achieved more citations per document than dense and compact networks – described by a high Clustering coefficient and a high Average degree. According to disciplinary differences, Mathematics, Social Sciences and Economics & Business are the disciplines with more sparse and tiny networks; while Physics, Engineering and Geosciences are characterized by dense and crowded networks. This suggests that in sparse ego networks, the central author have more control on their collaborators being more selective in their recruitment and concluding that this behaviour has positive implications in the research impact. Keywords: Bibliometrics; Academic search engines; Ego networks; Research impact; Co-authorship (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:8:y:2014:i:3:p:728-737 DOI: 10.1016/j.joi.2014.07.001 Access Statistics for this article Journal of Informetrics is currently edited by Leo Egghe More articles in Journal of Informetrics from Elsevier |
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