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EgoClustering: Overlapping Community Detection via Merged Friendship-Groups

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The Influence of Technology on Social Network Analysis and Mining

Part of the book series: Lecture Notes in Social Networks ((LNSN,volume 6))

Abstract

There has been considerable interest in identifying communities within large collections of social networking data. Existing algorithms will classify an actor (node) into a single group, ignoring the fact that in real-world situations people tend to belong concurrently to multiple (overlapping) groups. Our work focuses on the ability to find overlapping communities. We use egonets to form friendship-groups. A friendship-group is a localized community as seen from an individual’s perspective that allows an actor to belong to multiple communities. Our algorithm finds overlapping communities and identifies key members that bind communities together. Additionally, we will highlight the parallel feature of the algorithm as a means of improving runtime performance, and the ability of the algorithm to run within a database and not be constrained by system memory.

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Acknowledgements

The authors are grateful to Graham Cruickshank for his proofreading skill.

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Authors and Affiliations

  1. Department of Computer Science, Florida Institute of Technology, Melbourne, FL, USA

    Bradley S. Rees & Keith B. Gallagher

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  1. Bradley S. Rees
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  2. Keith B. Gallagher
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Correspondence to Bradley S. Rees .

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Editors and Affiliations

  1. Department of Computer Engineering, TOBB University, Sogutozu Cad No. 43, Sogutozu Ankara, Turkey

    Tansel Özyer

  2. Computer Science, University of Calgary, University Dr. NW 2500, Calgary, T2N 1N4, Canada

    Jon Rokne

  3. IPSC, European Commission Joint Research Cent., Via Enrico Fermi 2749, Ispra, 21027, Italy

    Gerhard Wagner

  4. De Wetstraat 16, Leiden, 2332 XT, Netherlands

    Arno H.P. Reuser

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Rees, B.S., Gallagher, K.B. (2013). EgoClustering: Overlapping Community Detection via Merged Friendship-Groups. In: Özyer, T., Rokne, J., Wagner, G., Reuser, A. (eds) The Influence of Technology on Social Network Analysis and Mining. Lecture Notes in Social Networks, vol 6. Springer, Vienna. https://doi.org/10.1007/978-3-7091-1346-2_1

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  • DOI: https://doi.org/10.1007/978-3-7091-1346-2_1

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  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-7091-1345-5

  • Online ISBN: 978-3-7091-1346-2

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