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

被引：101
作者：
Ghanem, Bilal [1 ]
Rosso, Paolo [1 ]
Rangel, Francisco [2 ]
机构：
[1] Univ Politecn Valencia, Valencia, Spain
[2] Symanto Res, Nurnberg, Germany
来源：
ACM TRANSACTIONS ON INTERNET TECHNOLOGY | 2020年 / 20卷 / 02期
关键词：
Fake news; suspicious news; false information; emotional analysis; FACT;
D O I：
10.1145/3381750
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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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页数：18
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