Detecting Search Engine Spam from a Trackback Network in Blogspace

Abstract. We aim to develop a technique to detect search engine optimization (SEO) spam websites. Specifically, we propose four methods for extracting the SEO spam entries from a given trackback network in blogspace that are based on fundamental metrics on a network. Using real data of trackback networks in blogspace, we experimentally evaluate the performance of the proposed methods, and demonstrate that the method of ranking entries based on average degrees of nearest neighbors can be a very promising approach for extracting SEO spam entries.

• Type: Conference
• Year: 2005
• Where: KES
• Authors: Masahiro Kimura, Kazumi Saito, Kazuhiro Kazama, Shin-ya Sato
• Keywords: KES 2005, Search Engine Optimization, SEO Spam Entries, Trackback Networks