Title :
An Unsupervised Approach for Identifying Spammers in Social Networks
Author :
Bouguessa, Mohamed
Author_Institution :
Dept. d´´Inf. et d´´Ing. Gatineau, Univ. du Quebec en Outaouais, Gatineau, QC, Canada
Abstract :
This paper proposes an unsupervised method for automatic identification of spammers in a social network. In our approach, we first investigate the link structure of the network in order to derive a legitimacy score for each node. Then we model these scores as a mixture of beta distributions. The number of components in the mixture is determined by the integrated classification likelihood Bayesian information criterion, while the parameters of each component are estimated using the expectation-maximization algorithm. This method allows us to automatically discriminate between spam senders and legitimate users. Experimental results show the suitability of the proposed approach and compare its performance to that of a previous fully-supervised method. We also illustrate our approach through a test application to Yahoo! Answers, a large question-answering web service that is particularly rich in the amount and types of content and social interactions represented.
Keywords :
Bayes methods; Web services; expectation-maximisation algorithm; question answering (information retrieval); social networking (online); unsolicited e-mail; unsupervised learning; Yahoo! Answers; beta distributions; content interactions; expectation-maximization algorithm; integrated classification likelihood Bayesian information criterion; legitimacy score; legitimate users; question-answering Web service; social interactions; social network analysis; spam senders; spammer automatic identification; unsupervised method; Clustering algorithms; Electronic mail; Feature extraction; Measurement; Partitioning algorithms; Shape; Social network services; beta mixture model; social networks; spammers identification; unsupervised learning;
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2011 23rd IEEE International Conference on
Conference_Location :
Boca Raton, FL
Print_ISBN :
978-1-4577-2068-0
Electronic_ISBN :
1082-3409
DOI :
10.1109/ICTAI.2011.130