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COTILES: Leveraging Content and Structure for Evolutionary Community Detection

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Book cover Transactions on Large-Scale Data- and Knowledge-Centered Systems XLV

Part of the book series: Lecture Notes in Computer Science ((TLDKS,volume 12390))

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Abstract

Most community detection algorithms for online social networks rely solely either on the structure of the network, or on its contents. Both extremes ignore valuable information that influences cluster formation. We propose COTILES, an evolutionary community detection algorithm, that leverages both structural and content-based criteria so as to derive densely connected communities with similar contents. Specifically, we extend a fast online structural community detection algorithm by applying additional content-based constraints. We also further explore the effect of structure and content-based criteria on the clustering result by introducing three tunable variations of COTILES that either tighten or relax these criteria. Through our experimental evaluation, we show that the proposed method derives more cohesive communities compared to the original structural one, and highlight when the proposed variations should be deployed.

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Authors and Affiliations

  1. Applied Informatics Department, University of Macedonia, Thessaloniki, 54636, Greece

    Nikolaos Sachpenderis, Georgia Koloniari & Alexandros Karakasidis

Authors
  1. Nikolaos Sachpenderis
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  2. Georgia Koloniari
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  3. Alexandros Karakasidis
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Corresponding author

Correspondence to Georgia Koloniari .

Editor information

Editors and Affiliations

  1. IRIT, Paul Sabatier University, Toulouse, France

    Abdelkader Hameurlain

  2. Vienna University of Technology, Vienna, Austria

    A Min Tjoa

  3. University of Pau and Pays de l'Adour, Anglet, France

    Richard Chbeir

  4. Open University of Cyprus, Nicosia, Cyprus

    Yannis Manolopoulos

  5. Tokyo Metropolitan University, Tokyo, Japan

    Hiroshi Ishikawa

  6. University of Zaragoza, Zaragoza, Spain

    Sergio Ilarri

  7. Aristotle University of Thessaloniki, Thessaloniki, Greece

    Apostolos Papadopoulos

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Sachpenderis, N., Koloniari, G., Karakasidis, A. (2020). COTILES: Leveraging Content and Structure for Evolutionary Community Detection. In: Hameurlain, A., et al. Transactions on Large-Scale Data- and Knowledge-Centered Systems XLV. Lecture Notes in Computer Science(), vol 12390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-62308-4_3

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  • DOI: https://doi.org/10.1007/978-3-662-62308-4_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-62307-7

  • Online ISBN: 978-3-662-62308-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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