Abstract
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.
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Notes
See data and interactive visualizations at http://info.slis.indiana.edu/~eyan/papers/cluster/.
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Acknowledgments
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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Yan, E., Ding, Y. & Jacob, E.K. Overlaying communities and topics: an analysis on publication networks. Scientometrics 90, 499–513 (2012). https://doi.org/10.1007/s11192-011-0531-6
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DOI: https://doi.org/10.1007/s11192-011-0531-6