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Revealing censored information through comments and commenters in online social networks

Cascavilla,Giuseppe
; 
Conti,Mauro
; 
Schwartz,David G.
; 
Yahav,Inbal
Abstract
In this work we study information leakage through discussions in online social networks. In particular, we focus on articles published by news pages, in which a person's name is censored, and we examine whether the person is identifiable (decensored) by analyzing comments and social network graphs of commenters. As a case study for our proposed methodology, in this paper we considered 48 articles (Israeli, military related) with censored content, followed by a threaded discussion. We qualitatively study the set of comments and identify comments (in this case referred as "leakers") and the commenter and the censored person. We denote these commenters as "leakers". We found that such comments are present for some 75% of the articles we considered. Finally, leveraging the social network graphs of the leakers, and specifically the overlap among the graphs of the leakers, we are able to identify the censored person. We show the viability of our methodology through some illustrative use cases.
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Publisher Copyright: © 2015 ACM.
Date
2015-08-25
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Association for Computing Machinery
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Tilburg University Research Output Collection
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Cascavilla, G, Conti, M, Schwartz, D G & Yahav, I 2015, Revealing censored information through comments and commenters in online social networks. in J Pei, J Tang & F Silvestri (eds), Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015. Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015, Association for Computing Machinery, pp. 675-680, IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015, Paris, France, 25/08/15. https://doi.org/10.1145/2808797.2809290
URI
https://hdl.handle.net/20.500.14602/25981
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