An Emotional Analysis of False Information in Social Media and News Articles

descriptionPublicationkeyboard_double_arrow_right Article , Preprint 19 Apr 2020Embargo end date: 01 Aug 2019 English Publisher:Association for Computing Machinery (ACM)Journal:ACM Transactions on Internet Technology, volume 20, pages 1-18 (issn: 1533-5399, eissn: 1557-6051,

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Authors: Bilal Ghanem; Paolo Rosso; Francisco M. Rangel Pardo;

doi: 10.1145/3381750 , 10.48550/arxiv.1908.09951

arXiv: 1908.09951

An Emotional Analysis of False Information in Social Media and News Articles

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Abstract

Fake news is risky, since it has been created to manipulate readers’ opinions and beliefs. In this work, we compared the language of false news to the real one of real news from an emotional perspective, considering a set of false information types (propaganda, hoax, clickbait, and satire) from social media and online news article sources. Our experiments showed that false information has different emotional patterns in each of its types, and emotions play a key role in deceiving the reader. Based on that, we proposed an LSTM neural network model that is emotionally infused to detect false news.

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Keywords

Social and Information Networks (cs.SI), FOS: Computer and information sciences, Computer Science - Computation and Language, Computer Science - Social and Information Networks, Computer Science - Information Retrieval, False information, Fake news, Suspicious news, Emotional analysis, LENGUAJES Y SISTEMAS INFORMATICOS, Computation and Language (cs.CL), Information Retrieval (cs.IR)

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