Security

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

Date Added: Nov 2009
Format: PDF

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.