Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (9): 99-105.DOI: 10.3778/j.issn.1002-8331.1901-0183

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Research on SNS Users’ Posting Behavior and Interest Prediction

HU Can, CUI Xiaohui   

  1. School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, China
  • Online:2020-05-01 Published:2020-04-29



  1. 武汉大学 国家网络安全学院,武汉 430072


Billions of users share their ideas through posting photos and texts on Social Network Services(SNSs). They are interested in various topics, usually have different sentiment tendencies and posting activities. This paper proposes a model to characterize SNS users’ posting activities for predicting users’ interests. Latent Dirichlet Allocation(LDA) is applied to discover typical patterns of users’ postings, such that one user’s posting sentiments are represented as probability distribution on the posting patterns. User behavior features are extracted from the LDA result, and combined with linguist features extracted from users’ likes pages to build an interest prediction model. The experiments results show that using user behavior features that characterized from users’ posting activities can improve the prediction accuracy.

Key words: user topology, interest prediction, sentiment analysis, user profiling, Latent Dirichlet Allocation(LDA) model



关键词: 用户拓扑, 兴趣预测, 情感分析, 用户画像, LDA模型