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The Author-Topic-Community model for author interest profiling and community discovery

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Abstract

In this paper, we propose a generative model named the author-topic-community (ATC) model for representing a corpus of linked documents. The ATC model allows each author to be associated with a topic distribution and a community distribution as its model parameters. A learning algorithm based on variational inference is derived for the model parameter estimation where the two distributions are essentially reinforcing each other during the estimation. We compare the performance of the ATC model with two related generative models using first synthetic data sets and then real data sets, which include a research community data set, a blog data set, a news-sharing data set, and a microblogging data set. The empirical results obtained confirm that the proposed ATC model outperforms the existing models for tasks such as author interest profiling and author community discovery. We also demonstrate how the inferred ATC model can be used to characterize the roles of users/authors in online communities.

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Notes

  1. An abridged version of this paper appears in [9].

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Acknowledgments

C. Li’s research is supported in part by NSFC under Grant No. 61370213, National Key Technology R&D Program No. 2012BAH10F03, 2013BAH17F00, Shenzhen Strategic Emerging Industries Program under Grant No. JCYJ20120613150552967 and Science and Technology Development of Shandong Province Nos. 2010GZX20126, 2010GGX10116.

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Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology, Weihai, China

    Chunshan Li & Dianhui Chu

  2. Department of Computer Science, Hong Kong Baptist University, Kowloon, Hong Kong SAR

    William K. Cheung

  3. Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen, China

    Yunming Ye & Xiaofeng Zhang

  4. Shenzhen Key Laboratory of Internet Information Collaboration, Shenzhen, China

    Yunming Ye & Xiaofeng Zhang

  5. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

    Xin Li

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  1. Chunshan Li
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  2. William K. Cheung
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  3. Yunming Ye
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  4. Xiaofeng Zhang
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  5. Dianhui Chu
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  6. Xin Li
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Correspondence to Xiaofeng Zhang.

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Li, C., Cheung, W.K., Ye, Y. et al. The Author-Topic-Community model for author interest profiling and community discovery. Knowl Inf Syst 44, 359–383 (2015). https://doi.org/10.1007/s10115-014-0764-9

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  • DOI: https://doi.org/10.1007/s10115-014-0764-9

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