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China Conference on Knowledge Graph and Semantic Computing

CCKS 2017: Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence pp 92–103Cite as

Micro-blog User Community Detection by Focusing on Micro-blog Content and Community Structure

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 784))

Abstract

Micro-blog community detection is one of the hot problems of Micro-blog platform. There are many existing community detection methods that are dedicated to detect community by only considering the topological structure. To detect Micro-blog community better, we considering the Micro-blog content as well as the topological structure. In Micro-blog community, the essence of a concept is semantic objects in the real world. The concept is composed of the object’s attribute set, and the attribute set is a set of nouns that essentially can represent the object. In this article, we let user be object and calculate the interest similarity by the object’s attribute set. First, we establish a micro-blog social network by analyzing the object’s attribute set. Second, we find the clustering directions for each object by the Random Walk method. Then, we detect micro-blog user community following the clustering directions. Finally, experiments performed to verify the efficiency of our method from the two aspects of community structure and interest cohesion.

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Acknowledgments

This work is supported by the National Nature Science Foundation (Grant No. 61271413, 61472329 and 61532009) and the Innovation Fund of Postgraduate, Xihua University.

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Authors and Affiliations

  1. School of Computer and Software Engineering, Xihua University, Chengdu, 610039, China

    Jia Liu & Ya-jun Du

  2. School of Political and Public Administration, Electronic Science and Technology University, Chengdu, 611731, China

    Ji-zhong Ren

Authors
  1. Jia Liu
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  2. Ya-jun Du
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  3. Ji-zhong Ren
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Corresponding author

Correspondence to Jia Liu .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Juanzi Li

  2. Beijing Xigema Center, Beijing, China

    Ming Zhou

  3. School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, China

    Guilin Qi

  4. Google, Mountain View, California, USA

    Ni Lao

  5. East China University of Science and Technology, Shanghai, China

    Tong Ruan

  6. Guangdong University of Foreign Studies, Guangzhou, China

    Jianfeng Du

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Liu, J., Du, Yj., Ren, Jz. (2017). Micro-blog User Community Detection by Focusing on Micro-blog Content and Community Structure. In: Li, J., Zhou, M., Qi, G., Lao, N., Ruan, T., Du, J. (eds) Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence. CCKS 2017. Communications in Computer and Information Science, vol 784. Springer, Singapore. https://doi.org/10.1007/978-981-10-7359-5_10

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  • DOI: https://doi.org/10.1007/978-981-10-7359-5_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7358-8

  • Online ISBN: 978-981-10-7359-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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