Sciweavers

Share
DBSEC
2010

Detecting Spam Bots in Online Social Networking Sites: A Machine Learning Approach

11 years 8 months ago
Detecting Spam Bots in Online Social Networking Sites: A Machine Learning Approach
As online social networking sites become more and more popular, they have also attracted the attentions of the spammers. In this paper, Twitter, a popular micro-blogging service, is studied as an example of spam bots detection in online social networking sites. A machine learning approach is proposed to distinguish the spam bots from normal ones. To facilitate the spam bots detection, three graph-based features, such as the number of friends and the number of followers, are extracted to explore the unique follower and friend relationships among users on Twitter. Three content-based features are also extracted from user's most recent 20 tweets. A real data set is collected from Twitter's public available information using two different methods. Evaluation experiments show that the detection system is efficient and accurate to identify spam bots in Twitter.
Alex Hai Wang
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2010
Where DBSEC
Authors Alex Hai Wang
Comments (0)
books