Overlaying communities and topics: an analysis on publication networks
ScientometricsPublished 8 October 2011
Erjia Yan, Ying Ding, Elin K. Jacob
Citations47
SJR quartileQ1
SJR score1.15
SNIP1.82
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TL;DR
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.
Abstract
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.
Keywords
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