Affiliation:
1. Universitat Politècnica de València, Valencia, Spain
2. Symanto Research, Nürnberg, Germany
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.
Funder
Spanish MICINN
MISMIS-FAKEnHATE on Misinformation
Miscommunication in social media: FAKEnews and HATE speech
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Networks and Communications
Cited by
100 articles.
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