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Community Verification with Topic Modeling

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Wireless Algorithms, Systems, and Applications (WASA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10251))

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Abstract

Different performance measurement metrics have been proposed to evaluate the performance of community detection algorithms, such as modularity, conductance, etc. However, there is few work which makes sense of a community, that is, explain what does the community do, what is the community’s interest. In this paper, we use topic modeling to capture the topics of users in the same community and verify a heuristic community detection algorithm by showing that the users in the communities share strong interests.

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Acknowledgments

This project is supported by NSF grant CNS #1218212.

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Authors and Affiliations

  1. School of Mathematical and Natural Sciences, Arizona State University, Tempe, USA

    Feng Wang & Ken Orton

Authors
  1. Feng Wang
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  2. Ken Orton
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Corresponding author

Correspondence to Feng Wang .

Editor information

Editors and Affiliations

  1. Texas Christian University, Fort Worth, Texas, USA

    Liran Ma

  2. New Jersey Institute of Technology, Newark, New Jersey, USA

    Abdallah Khreishah

  3. University of Oslo, Oslo, Norway

    Yan Zhang

  4. University of North Georgia, Dahlonega, Georgia, USA

    Mingyuan Yan

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Wang, F., Orton, K. (2017). Community Verification with Topic Modeling. In: Ma, L., Khreishah, A., Zhang, Y., Yan, M. (eds) Wireless Algorithms, Systems, and Applications. WASA 2017. Lecture Notes in Computer Science(), vol 10251. Springer, Cham. https://doi.org/10.1007/978-3-319-60033-8_25

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  • DOI: https://doi.org/10.1007/978-3-319-60033-8_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60032-1

  • Online ISBN: 978-3-319-60033-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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