Linguistic signals under misinformation and fact-checking: Evidence from user comments on social media

被引：25

作者：

Jiang S. ^{[1
]}

Wilson C. ^{[1
]}

机构：

[1] Northeastern University, United States

来源：

Proceedings of the ACM on Human-Computer Interaction | 2018年 / 2卷 / CSCW期

关键词：

Fact-checking; Fake news; Misinformation; Social computing; Social media;

D O I：

10.1145/3274351

中图分类号：

学科分类号：

摘要：

Misinformation and fact-checking are opposite forces in the news environment: The former creates inaccuracies to mislead people, while the latter provides evidence to rebut the former. These news articles are often posted on social media and attract user engagement in the form of comments. In this paper, we investigate linguistic (especially emotional and topical) signals expressed in user comments in the presence of misinformation and fact-checking. We collect and analyze a dataset of 5,303 social media posts with 2,614,374 user comments from Facebook, Twitter, and YouTube, and associate these posts to fact-check articles from Snopes and PolitiFact for veracity rulings (i.e., from true to false). We find that linguistic signals in user comments vary significantly with the veracity of posts, e.g., we observe more misinformation-awareness signals and extensive emoji and swear word usage with falser posts. We further show that these signals can help to detect misinformation. In addition, we find that while there are signals indicating positive effects after fact-checking, there are also signals indicating potential “backfire” effects. © 2018 Copyright held by the owner/author(s). Publication rights licensed to the Association for Computing Machinery.

引用

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