[1]KONG Qingchao,MAO Wenji,ZHANG Yuhao.User comment behavior prediction in social networking sites[J].CAAI Transactions on Intelligent Systems,2015,10(3):349-353.[doi:10.3969/j.issn.1673-4785.201403019]
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User comment behavior prediction in social networking sites

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 10 Number of periods: 2015 3 Page number: 349-353 Column: 学术论文—自然语言处理与理解 Public date: 2015-06-25
Title:
User comment behavior prediction in social networking sites
Author(s):
KONG Qingchao;  MAO Wenji;  ZHANG Yuhao
State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Science, Beijing 100190, China
Keywords:
social network; user comments; machine learning; behavior modeling; behavior prediction; imbalance dataset
CLC:
TP391
DOI:
10.3969/j.issn.1673-4785.201403019
Abstract:
Social networking sites provide a convenient way for users to communicate with others and to present opinions. Related researches on modeling and predicting user behaviors in social networking sites are of vital importance for many applications in the domains of security and business. The aim of this paper is to predict user comment behavior based on postings in social networking sites. A feature-based machine learning approach is employed, which includes features from the postings, content, user behaviors and social relations, and introduces a parameter to control the imbalanceness of the dataset. Real-world datasets from Douban Group were used in the experiments. The experimental results showed that the user behavior and social relation features and the imbalance processing technique effectively improved the prediction performance of user comment behaviors. This further demonstrates that the user comment behavior is largely affected by their behavior history and social network.
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