Publication Date
Fall 2009
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
Advisor
Teng-Sheng Moh
Subject Areas
Information Technology.; Artificial Intelligence.; Computer Science.
Abstract
As online social networks acquire larger user bases, they also become more interesting targets for spammers. Spam can take very different forms on social Web sites and cannot always be detected by analyzing textual content. However, the platform's social nature also offers new ways of approaching the spam problem. In this work the possibilities of analyzing a user's direct neighbors in the social graph to improve spammer detection are explored. Special features of social Web sites and their implicit trust relations are utilized to create an enhanced attribute set that categorizes users on the Twitter microblogging platform as spammers or legitimate users.
Recommended Citation
Murmann, Alexander J., "Enhancing spammer detection in online social networks with trust-based metrics." (2009). Master's Theses. 3985.
DOI: https://doi.org/10.31979/etd.yv9m-vfvb
https://scholarworks.sjsu.edu/etd_theses/3985
