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

Published:19 April 2020Publication History
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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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      • Published in

        cover image ACM Transactions on Internet Technology
        ACM Transactions on Internet Technology  Volume 20, Issue 2
        Special Section on Emotions in Conflictual Social Interactions and Regular Papers
        May 2020
        256 pages
        ISSN:1533-5399
        EISSN:1557-6051
        DOI:10.1145/3386441
        • Editor:
        • Ling Liu
        Issue’s Table of Contents

        Copyright © 2020 ACM

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 19 April 2020
        • Accepted: 1 January 2020
        • Revised: 1 December 2019
        • Received: 1 July 2019
        Published in toit Volume 20, Issue 2

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