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Cited by 125Misinformation and Its ImpactsSpam and Phishing DetectionHate Speech and Cyberbullying Detection

Linguistic Signals under Misinformation and Fact-Checking: Evidence from User Comments on Social Media

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Jiang, Shan, Wilson, Christo·2018·Proceedings of the ACM on Human-Computer Interaction
DOI 10.1145/3274351
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Abstract

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.

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Authors
Jiang, S., & Wilson, C.
Affiliations
Northeastern University (US)
ORCID
Wilson, Christo
Venue
Proceedings of the ACM on Human-Computer Interaction
Publisher
Association for Computing Machinery (ACM)
Published
2018-11
Volume
2
Issue
CSCW
Pages
1-23
ISSN
2573-0142 (ISSN-L)
DOI
10.1145/3274351
OpenAlex
W2899024559
Cited by
125
References
110
Citations by year
2026: 6 · 2025: 13 · 2024: 26 · 2023: 15 · 2022: 13 · 2021: 20 · 2020: 22 · 2019: 9 · 2018: 1
FWCI
29.59
Type
journal article
Language
en
Open access
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations
Proceedings of the ACM on Human-Computer Interaction (publishedVersion)
Funders
  • National Science Foundation (IIS-1408345)
  • NSF (IIS-1553088)
Topics
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
  • Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
  • Physical Sciences › Computer Science › Artificial Intelligence › Hate Speech and Cyberbullying Detection
Keywords
misinformation, fact-checking, online comments, social media, linguistic signals, emotional signals, emoji usage, swearing, misinformation awareness, misinformation detection, backfire effect, honesty, Snopes, PolitiFact

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