Overlaying communities and topics: an analysis on publication networks

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...

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Bibliographic Details
Published inScientometrics Vol. 90; no. 2; pp. 499 - 513
Main Authors Yan, Erjia, Ding, Ying, Jacob, Elin K.
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.02.2012
Springer
Subjects
Bibliometrics
Bibliometrics. Scientometrics
Bibliometrics. Scientometrics. Evaluation
Computer Science
Exact sciences and technology
Information and communication sciences
Information science. Documentation
Information Storage and Retrieval
Library and information science. General aspects
Library Science
Networks
Scholarly publishing
Sciences and techniques of general use
Subject fields
Topic
Detection
Scholarly networks
Community
Webometrics
Cluster
Scientific publication
Bibliometric analysis
Bibliometrics
Informetrics
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Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0138-9130
1588-2861
DOI:10.1007/s11192-011-0531-6