NewsVallum: Semantics-Aware Text and Image Processing for Fake News Detection system

Giuliano Armano;Sebastiano Battiato;Davide Bennato;Ludovico Boratto;Salvatore M. Carta;Tommaso Di Noia;Eugenio Di Sciascio;Alessandro Ortis;Diego Reforgiato Recupero

2018-01-01

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Abstract

As a consequence of the social revolution we faced on the Web, news and information we daily enjoy may come from different and diverse sources which are not necessarily the traditional ones such as newspapers, either in their paper or online version, television, radio, etc. Everyone on the Web is allowed to produce and share news which can soon become viral if they follow the new media channels represented by social networks. This freedom in producing and sharing news comes with a counter-effect: the proliferation of fake news. Unfortunately, they can be very effective and may influence people and, more generally, the public opinion. We propose a combined approach of natural language and image processing that takes into account the semantics encoded within both text and images coming with news together with contextual information that may help in the classification of a news as fake or not.