Communications of the ACM
Fighting Spam on Social Web Sites: A Survey of Approaches and Future Challenges
IEEE Internet Computing
Combating spam in tagging systems: An evaluation
ACM Transactions on the Web (TWEB)
Social networks and context-aware spam
Proceedings of the 2008 ACM conference on Computer supported cooperative work
Detecting spammers and content promoters in online video social networks
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Uncovering social spammers: social honeypots + machine learning
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
@spam: the underground on 140 characters or less
Proceedings of the 17th ACM conference on Computer and communications security
Detecting product review spammers using rating behaviors
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Predicting popular messages in Twitter
Proceedings of the 20th international conference companion on World wide web
Proceedings of the 20th international conference companion on World wide web
Information credibility on twitter
Proceedings of the 20th international conference on World wide web
Proceedings of the 20th international conference on World wide web
Distortion as a validation criterion in the identification of suspicious reviews
Proceedings of the First Workshop on Social Media Analytics
Reverse social engineering attacks in online social networks
DIMVA'11 Proceedings of the 8th international conference on Detection of intrusions and malware, and vulnerability assessment
Content-driven detection of campaigns in social media
Proceedings of the 20th ACM international conference on Information and knowledge management
Predicting semantic annotations on the real-time web
Proceedings of the 23rd ACM conference on Hypertext and social media
Twitter games: how successful spammers pick targets
Proceedings of the 28th Annual Computer Security Applications Conference
REPLOT: REtrieving profile links on Twitter for suspicious networks detection
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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We examine the problem of collective attention spam, in which spammers target social media where user attention quickly coalesces and then collectively focuses around a phenomenon. Compared to many existing spam types, collective attention spam relies on the users themselves to seek out the content -- like breaking news, viral videos, and popular memes -- where the spam will be encountered, potentially increasing its effectiveness and reach. We study the presence of collective attention spam in one popular service, Twitter, and we develop spam classifiers to detect spam messages generated by collective attention spammers. Since many instances of collective attention are bursty and unexpected, it is difficult to build spam detectors to pre-screen them before they arise; hence, we examine the effectiveness of quickly learning a classifier based on the first moments of a bursting phenomenon. Through initial experiments over a small set of trending topics on Twitter, we find encouraging results, suggesting that collective attention spam may be identified early in its life cycle and shielded from the view of unsuspecting social media users.