Kolari, PranamJava, AkshayFinin, TimOates, TimJoshi, Anupam2018-12-072018-12-072006-07-16Pranam Kolari, Akshay Java, Tim Finin, Tim Oates, and Anupam Joshi, Detecting Spam Blogs: A Machine Learning Approach, Proceedings of the 21st National Conference on Artificial Intelligence (AAAI 2006), https://www.aaai.org/Papers/AAAI/2006/AAAI06-212.pdfhttp://hdl.handle.net/11603/12192Proceedings of the 21st National Conference on Artificial Intelligence (AAAI 2006)Weblogs or blogs are an important new way to publish information, engage in discussions, and form communities on the Internet. The Blogosphere has unfortunately been infected by several varieties of spam-like content. Blog search engines, for example, are inundated by posts from splogs – false blogs with machine generated or hijacked content whose sole purpose is to host ads or raise the PageRank of target sites. We discuss how SVM models based on local and link-based features can be used to detect splogs. We present an evaluation of learned models and their utility to blog search engines; systems that employ techniques differing from those of conventional web search engines. We evaluate the effectiveness of a combination of features, and finally report our informal analysis of a blog search engine index.6 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.bloglearningsocial mediaspamweb spammachine learningUMBC Ebiquity Research GroupDetecting Spam Blogs: A Machine Learning ApproachText