Convex Optimization
Multi-label informed latent semantic indexing
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Learning from labeled and unlabeled data on a directed graph
ICML '05 Proceedings of the 22nd international conference on Machine learning
Social networks and context-aware spam
Proceedings of the 2008 ACM conference on Computer supported cooperative work
All your contacts are belong to us: automated identity theft attacks on social networks
Proceedings of the 18th international conference on World wide web
An accelerated gradient method for trace norm minimization
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Exploiting internal and external semantics for the clustering of short texts using world knowledge
Proceedings of the 18th ACM conference on Information and knowledge management
TwitterRank: finding topic-sensitive influential twitterers
Proceedings of the third ACM international conference on Web search and data mining
Multi-task feature learning via efficient l2, 1-norm minimization
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
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
Truthy: mapping the spread of astroturf in microblog streams
Proceedings of the 20th international conference companion on World wide web
Towards feature selection in network
Proceedings of the 20th ACM international conference on Information and knowledge management
Suspended accounts in retrospect: an analysis of twitter spam
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Uncovering social network sybils in the wild
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Understanding and combating link farming in the twitter social network
Proceedings of the 21st international conference on World Wide Web
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The availability of microblogging, like Twitter and Sina Weibo, makes it a popular platform for spammers to unfairly overpower normal users with unwanted content via social networks, known as social spamming. The rise of social spamming can significantly hinder the use of microblogging systems for effective information dissemination and sharing. Distinct features of microblogging systems present new challenges for social spammer detection. First, unlike traditional social networks, microblogging allows to establish some connections between two parties without mutual consent, which makes it easier for spammers to imitate normal users by quickly accumulating a large number of "human" friends. Second, microblogging messages are short, noisy, and unstructured. Traditional social spammer detection methods are not directly applicable to microblogging. In this paper, we investigate how to collectively use network and content information to perform effective social spammer detection in microblogging. In particular, we present an optimization formulation that models the social network and content information in a unified framework. Experiments on a real-world Twitter dataset demonstrate that our proposed method can effectively utilize both kinds of information for social spammer detection.