DocumentCode
2399759
Title
Finding Overlapping Communities in Social Networks
Author
Goldberg, Mark ; Kelley, Stephen ; Magdon-Ismail, Malik ; Mertsalov, Konstantin ; Wallace, Al
Author_Institution
Dept. of Comput. Sci., Rensselaer Polytech. Inst., Troy, NY, USA
fYear
2010
fDate
20-22 Aug. 2010
Firstpage
104
Lastpage
113
Abstract
Increasingly, methods to identify community structure in networks have been proposed which allow groups to overlap. These methods have taken a variety of forms, resulting in a lack of consensus as to what characteristics overlapping communities should have. Furthermore, overlapping community detection algorithms have been justified using intuitive arguments, rather than quantitative observations. This lack of consensus and empirical justification has limited the adoption of methods which identify overlapping communities. In this text, we distil from previous literature a minimal set of axioms which overlapping communities should satisfy. Additionally, we modify a previously published algorithm, Iterative Scan, to ensure that these properties are met. By analyzing the community structure of a large blog network, we present both structural and attribute based verification that overlapping communities naturally and frequently occur.
Keywords
information retrieval; social networking (online); attribute based verification; blog network; intuitive arguments; iterative scan; overlapping community detection algorithms; social network analysis; Algorithm design and analysis; Communities; Information services; Internet; Measurement; Partitioning algorithms; Social network services; community detection; overlapping groups; social network analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Social Computing (SocialCom), 2010 IEEE Second International Conference on
Conference_Location
Minneapolis, MN
Print_ISBN
978-1-4244-8439-3
Electronic_ISBN
978-0-7695-4211-9
Type
conf
DOI
10.1109/SocialCom.2010.24
Filename
5590817
Link To Document