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.
Carchiolo, V., Longheu, A., Malgeri, M., Mangioni, G., & Previti, M. (2017). Post sharing-based credibility network for social network. Studies in Computational Intelligence, 737, 149–158. https://doi.org/10.1007/978-3-319-66379-1_14