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ICMCS
2007
IEEE

Splog Detection using Content, Time and Link Structures

12 years 4 months ago
Splog Detection using Content, Time and Link Structures
This paper focuses on spam blog (splog) detection. Blogs are highly popular, new media social communication mechanisms and splogs corrupt blog search results as well as waste network resources. In our approach we exploit unique blog temporal dynamics to detect splogs. The key idea is that splogs exhibit high temporal regularity in content and post time, as well as consistent linking patterns. Temporal content regularity is detected using a novel autocorrelation of post content. Temporal structural regularity is determined using the entropy of the post time difference distribution, while the link regularity is computed using a HITS based hub score measure. Experiments based on the annotated ground truth on real world dataset show excellent results on splog detection tasks with 90% accuracy.
Yu-Ru Lin, Hari Sundaram, Yun Chi, Jun'ichi Tatemu
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where ICMCS
Authors Yu-Ru Lin, Hari Sundaram, Yun Chi, Jun'ichi Tatemura, Belle L. Tseng
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