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
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;
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
DOI :
10.1109/SocialCom.2010.24