JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2017, Vol. 52 ›› Issue (7): 97-103.doi: 10.6040/j.issn.1671-9352.1.2016.007

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A community division method based on network distance and content similarity in micro-blog social network

ZHANG Zhong-jun1,2, ZHANG Wen-juan1, YU Lai-hang1,3, LI Run-chuan4,5   

  1. 1. School of Computer Science and Technology of Zhoukou Normal University, Zhoukou 466001, Henan, China;
    2. Traceability Technology of Agricultural products quality and Safety Engineering Laboratory of Henan Provincial, Zhoukou 466001, Henan, China;
    3. School of Computer Science and Technology of Dalian University of Technology, Dalian 116024, Liaoning, China;
    4. Collaborative Innovation Center of Internet Medical and Healthcare in Henan, Zhengzhou 450000, Henan, China;
    5. Institute of industrial technology, Zhengzhou University, Zhengzhou 450000, Henan, China
  • Received:2016-11-25 Online:2017-07-20 Published:2017-07-07

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Abstract: Existing micro-blog social network community mining methods are based on the network structure, ignoring the importance of nodes behavior, and can not guarantee the adaptability on large-scale complex network structure and the efficiency of community mining. To alleviate these problems, a new method ABDC is proposed for the community network of micro-blog based on the network distance and content similarity, the method considers the structure of the social network of micro-blog at the same time taking into account the historical blog content of the node in the network, improved the accuracy of community division through analysis the historical micro-blog data, In this paper, the Louvain algorithm and its modularity are modified and used to ensure that the method can deal with large scale network data, and 山 东 大 学 学 报 (理 学 版)第52卷 - 第7期张中军,等:基于网络距离和内容相似度的微博社交网络社区划分方法 \=-get high efficiency of community mining. Experiments show that the method can efficiently mine the community structure of micro-blog network, which has great significance for academic research and business applications.

Key words: micro-blog, social network, modularity, community

CLC Number: 

  • TP311
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