Abstract
In the Web 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%). © 2010 Springer-Verlag.
Cite
CITATION STYLE
Huang, C., Jiang, Q., & Zhang, Y. (2010). Detecting comment spam through content analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6185 LNCS, pp. 222–233). https://doi.org/10.1007/978-3-642-16720-1_23
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