12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China

Research Article

Cross-social-network Interconnection Model Based on Bridge Community

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  • @INPROCEEDINGS{10.4108/eai.29-6-2019.2282012,
        author={min  hu and mengyuan  dong},
        title={Cross-social-network Interconnection Model Based on Bridge Community},
        proceedings={12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China},
        publisher={EAI},
        proceedings_a={MOBIMEDIA},
        year={2019},
        month={6},
        keywords={cross-social-network interconnection model information mining bridge community},
        doi={10.4108/eai.29-6-2019.2282012}
    }
    
  • min hu
    mengyuan dong
    Year: 2019
    Cross-social-network Interconnection Model Based on Bridge Community
    MOBIMEDIA
    EAI
    DOI: 10.4108/eai.29-6-2019.2282012
min hu1,*, mengyuan dong1
  • 1: School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications
*Contact email: humin@cqupt.edu.cn

Abstract

As users participate in many online social networks (OSNs), connecting different social networks has become the latest task that researchers are focusing on. The analysis of user behavior needs to mine user information from multiple social networks, obtain more accurate information through association matching to analyze and predict, and improve the attributes of users' multiple social networks. Through the mining and analysis of user information, the interconnection of information dissemination of multiple social networks is realized. This paper firstly sorts the importance of user nodes in multi-social networks, and finds important nodes and secondarily important nodes to form the initial bridge community; then we build bridge user links through similarity matching of the users in the bridge community; finally, we propose cross-social-network interconnection model based on bridge community to enhance the structural interconnection between multiple social networks.