Splog Detection Using Self-similarity Analysis on Blog Temporal Dynamics

This paper focuses on spam blog (splog) detection. Blogs are highly popular, new media social communication mechanisms. The presence of splogs degrades blog search results as well as wastes network resources. In our approach we exploit unique blog temporal dynamics to detect splogs. There are three key ideas in our splog detection framework. We first represent the blog temporal dynamics using self-similarity matrices defined on the histogram intersection similarity measure of the time, content, and link attributes of posts. Second, we show via a novel visualization that the blog temporal characteristics reveal attribute correlation, depending on type of the blog (normal blogs and splogs). Third, we propose the use of temporal structural properties computed from self-similarity matrices across different attributes. In a splog detector, these novel features are combined with content based features. We extract a content based feature vector from different parts of the blog – URLs, post...

• Type: Conference
• Year: 2007
• Where: AIRWEB
• Authors: Yu-Ru Lin, Hari Sundaram, Yun Chi, Jun'ichi Tatemura, Belle L. Tseng
• Keywords: AIRWEB 2007, Blog, Blog Temporal Dynamics, Internet Technology, Self-similarity Matrices