Social networks are intensively and extensively used to exchange news and contents in real time. The lack of a global authority for assessing posts truthfulness however allows malicious to exhibit unfair behaviours; identifying methodologies to detect hoaxes and defamatory content automatically is therefore more and more required. Social networks as Facebook and Twitter provided specific solutions and general approaches were also developed; in this paper we present a general model that takes into account both post as well as users’ credibility, using a duplex network of acquaintances and credibility among users. First experiments show that it is possible to distinguish individuals who post non-truthful content through a combined analysis of both the news content and the reposts they get from their contacts.

Post sharing-based credibility network for social network

Carchiolo, V.;Longheu, A.;Malgeri, M.;Mangioni, G.;PREVITI, MARIALAURA
2017-01-01

Abstract

Social networks are intensively and extensively used to exchange news and contents in real time. The lack of a global authority for assessing posts truthfulness however allows malicious to exhibit unfair behaviours; identifying methodologies to detect hoaxes and defamatory content automatically is therefore more and more required. Social networks as Facebook and Twitter provided specific solutions and general approaches were also developed; in this paper we present a general model that takes into account both post as well as users’ credibility, using a duplex network of acquaintances and credibility among users. First experiments show that it is possible to distinguish individuals who post non-truthful content through a combined analysis of both the news content and the reposts they get from their contacts.
2017
978-3-319-66378-4
978-3-319-66379-1
Credibility; Social contagion; Social network; Artificial Intelligence
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/320863
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