A Co-Classification Framework for Detecting Web Spam and Spammers in Social Media Web Sites

Source: Association for Computing Machinery

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Social media are becoming increasingly popular and have attracted considerable attention from spammers. Using a sample of more than ninety thousand known spam Web sites, the authors found between 7% to 18% of their URLs are posted on two popular social media Web sites, digg.com and delicious.com. In this paper, the authors present a co-classification framework to detect Web spam and the spammers who are responsible for posting them on the social media Web sites.
Format:PDF Size:242.20
Date:Nov 2009