AAAI Spring Symposium on Computational Approaches to Analysing Weblogs

SVMs for the Blogosphere: Blog Identification and Splog Detection

Pranam Kolari, Tim Finin, and Anupam Joshi

March 27, 2006

Weblogs, or blogs have become an important new way to publish information, engage in discussions and form communities. The increasing popularity of blogs has given rise to search and analysis engines focusing on the 'blogosphere'. A key requirement of such systems is to identify blogs as they crawl the Web. While this ensures that only blogs are indexed, blog search engines are also often overwhelmed by spam blogs (splogs). Splogs not only incur computational overheads but also reduce user satisfaction. In this paper we first describe our experiments on blog identification using Support Vector Machines (SVM). We compare results of using different feature sets and introduce new features for blog identification. We then report preliminary results on splog detection and identify future work.

BibTeX OWL Tweet Scholar

Tags: blog, blog, blog, blogosphere, categorization, learning, metadata, spam, splog, splog, web spam

Type: InProceedings

Publisher: University of Maryland, Baltimore County

Organization: Computer Science and Electrical Engineering

Note: Also available as technical report TR-CS-05-13

Downloads: 14454 downloads

Google Scholar Citations: 112 citations