Overlaying communities and topics: an analysis on publication networks
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Two layers of enriched information are constructed for communities: a paper-to-paper network based on shared author relations and a paper-to-paper network based on shared word relations. k-means and VOSviewer, a modularity-based clustering technique, are used to identify publication clusters in the two networks. Results show that a few research topics such as webometrics, bibliometric laws, and language processing, form their own research community; while other research topics contain different research communities, which may be caused by physical distance.
KeywordsCommunity Topic Detection Scholarly networks
The authors would like to thank Ludo Waltman, Nees van Eck, and Ed Noyons for introducing VOSviewer and their comments to the idea of this paper.
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