Supervised Classification of Social Spammers using a Similarity-based Markov Random Field Approach-Reference-Cited by-同舟云学术

Supervised Classification of Social Spammers using a Similarity-based Markov Random Field Approach

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 5th Multidisciplinary International Social Networks Conference on - MISNC '18
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Author:

El-Mawass Nour¹,Honeine Paul¹,Vercouter Laurent²

Affiliation:

1. Normandie Univ, UNIROUEN, LITIS, Rouen, France

2. Normandie Univ, INSA Rouen, LITIS, Rouen, France

Publisher

ACM Press

Reference38 articles.

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3. Fabricio Benevenuto, Gabriel Magno, Tiago Rodrigues, and Virgilio Almeida. 2010. Detecting spammers on twitter. In Collaboration, electronic messaging, anti-abuse and spam conference (CEAS), Vol. 6. 12.

4. Alex Beutel, Wanhong Xu, Venkatesan Guruswami, Christopher Palow, and Christos Faloutsos. 2013. CopyCatch: stopping group attacks by spotting lockstep behavior in social networks. In Proceedings of the 22nd international conference on World WideWeb. InternationalWorld WideWeb Conferences Steering Committee, 119--130.

5. Sajid Yousuf Bhat and Muhammad Abulaish. 2013. Community-based features for identifying spammers in online social networks. Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining - ASONAM '13 (2013), 100--107. https://doi.org/10.1145/2492517.2492567

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