Detecting comment spam through content analysis

Authors:
Congrui Huang;Qiancheng Jiang;Yan Zhang
Affiliations:
Key Laboratory of Machine Perception, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing;Key Laboratory of Machine Perception, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing;Key Laboratory of Machine Perception, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing
Venue:
WAIM'10 Proceedings of the 2010 international conference on Web-age information management
Year:
2010

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Abstract

In theWeb 2.0 eras, the individual Internet users can also act as information providers, releasing information or making comments conveniently. However, some participants may spread irresponsible remarks or express irrelevant comments for commercial interests. This kind of so-called comment spam severely hurts the information quality. This paper tries to automatically detect comment spam through content analysis, using some previously-undescribed features. Experiments on a real data set show that our combined heuristics can correctly identify comment spam with high precision(90.4%) and recall(84.5%).