User communities and contents co-ranking for user-generated content quality evaluation in social networks

作者：Li, Lei^*; Lin, Xin; Zhai, Yue; Yuan, Caixia; Zhou, Yanquan; Qi, Jiayin

来源：International Journal of Communication Systems, 2016, 29(14): 2147-2168.

DOI：10.1002/dac.2908

• social network analysis
• user-generated content (UGC)
• quality evaluation
• user communities and contents co-ranking (UCCC)
• user community detection

With the massive popularity of social networks, more and more users can produce millions of user-generated contents (UGCs) daily. However, UGC quality is uneven, which has posed challenges to finding superior contents in such a large data set. In this paper, we present a new idea of UGC quality evaluation exploiting user communities, which are formed by users either in a friend circle or with similar interests in social networks. The intuition is that a user community can help evaluate the UGC quality better than a single user. Hence, we propose a new graph-theoretic user communities and contents co-ranking (UCCC) algorithm for UGC quality evaluation. UCCC evaluates UGCs and their related user communities simultaneously based on three different relationship networks: the network connecting UGCs, the network connecting user communities, and a third network that ties the two together. Contents and user communities are ranked following a co-ranking algorithm based on the assumption that there is a mutually reinforcing relationship between them. Experiments using real-world data have shown that UCCC outperforms competitive algorithms by a good margin in most cases and a user community is more useful than a single user for UGC quality evaluation.

• 出版日期2016-9-25
• 单位北京邮电大学