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A Two-Stage Overlapping Community Detection Based on Structure and Node Attributes in Online Social Networks

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Human Brain and Artificial Intelligence (HBAI 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1072))

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Abstract

Traditional community detection algorithms are mainly based on network structure, while ignoring a large number of node attributes. In this paper, we propose a two-stage overlapping community detection method which combines structure and attributes(tsocd-SA). First, a set of non-overlapping communities are identified by using existing community detection methods, and community attribute summaries which represents high degree homogeneous attribute value of a community are constructed according to the attributes of the special nodes in the community. Then, we propose a similarity measure between node and community based on network structure and community attribute summary. For connector nodes which connect more than one communities, each node is divided into one or more communities based on the similarity and a specific threshold r. Experimental results in online social network datasets show that our proposed method is more effective than solely focus on structural information.

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Acknowledgments

This research is supported by the National Natural Science Foundation of China (No. 62877013, 61402119).

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Authors and Affiliations

  1. Laboratory of Language Engineering and Computing, Guangdong University of Foreign Studies, Guangzhou, 510006, Guangdong, China

    Xinmeng Zhang & Xinguang Li

  2. Non-universal Language Intelligent Processing Laboratory, Guangdong University of Foreign Studies, Guangzhou, 510006, Guangdong, China

    Xinmeng Zhang, Shengyi Jiang, Xia Li & Bolin Xie

  3. School of Information Science and Technology, Guangdong University of Foreign Studies, Guangzhou, 510006, Guangdong, China

    Xinmeng Zhang, Shengyi Jiang, Xia Li & Bolin Xie

Authors
  1. Xinmeng Zhang
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  2. Xinguang Li
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  3. Shengyi Jiang
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  4. Xia Li
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  5. Bolin Xie
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Corresponding author

Correspondence to Xinmeng Zhang .

Editor information

Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    An Zeng

  2. Guangdong Construction Polytechnic, Guangzhou, China

    Dan Pan

  3. South China Normal University, Guangzhou, China

    Tianyong Hao

  4. Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Daoqiang Zhang

  5. University of Notre Dame, South Bend, IN, USA

    Yiyu Shi

  6. Simon Fraser University, Vancouver, BC, Canada

    Xiaowei Song

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Zhang, X., Li, X., Jiang, S., Li, X., Xie, B. (2019). A Two-Stage Overlapping Community Detection Based on Structure and Node Attributes in Online Social Networks. In: Zeng, A., Pan, D., Hao, T., Zhang, D., Shi, Y., Song, X. (eds) Human Brain and Artificial Intelligence. HBAI 2019. Communications in Computer and Information Science, vol 1072. Springer, Singapore. https://doi.org/10.1007/978-981-15-1398-5_23

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  • DOI: https://doi.org/10.1007/978-981-15-1398-5_23

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1397-8

  • Online ISBN: 978-981-15-1398-5

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