Overlapping community detection in rating-based social networks through analyzing topics, ratings and links
作者：
Highlights：
• A generic framework is proposed for community detection in social networks with special focus on rating-based social networks.
• The framework finds the overlapping communities in which the members are interested in the same topic, and the strengths of their relationships are based on the rate of their viewpoints’ unity.
• A novel weighting strategy for rating-based social networks is proposed which performs based on value of ratings.
• Quantitative evaluations show that the proposed framework has better performance than 3 other relevant frameworks.
摘要
•A generic framework is proposed for community detection in social networks with special focus on rating-based social networks.•The framework finds the overlapping communities in which the members are interested in the same topic, and the strengths of their relationships are based on the rate of their viewpoints’ unity.•A novel weighting strategy for rating-based social networks is proposed which performs based on value of ratings.•Quantitative evaluations show that the proposed framework has better performance than 3 other relevant frameworks.
论文关键词：Overlapping community detection,Content analysis,Topical community,Semantic network,Rating-based social networks
论文评审过程：Received 24 August 2017, Revised 14 November 2017, Accepted 11 April 2018, Available online 12 April 2018, Version of Record 21 April 2018.
论文官网地址：https://doi.org/10.1016/j.patcog.2018.04.013
