The Rise of Guardians: Fact-checking URL Recommendation to Combat Fake News
arXiv:1806.07516
Abstract
A large body of research work and efforts have been focused on detecting fake news and building online fact-check systems in order to debunk fake news as soon as possible. Despite the existence of these systems, fake news is still wildly shared by online users. It indicates that these systems may not be fully utilized. After detecting fake news, what is the next step to stop people from sharing it? How can we improve the utilization of these fact-check systems? To fill this gap, in this paper, we (i) collect and analyze online users called guardians, who correct misinformation and fake news in online discussions by referring fact-checking URLs; and (ii) propose a novel fact-checking URL recommendation model to encourage the guardians to engage more in fact-checking activities. We found that the guardians usually took less than one day to reply to claims in online conversations and took another day to spread verified information to hundreds of millions of followers. Our proposed recommendation model outperformed four state-of-the-art models by 11%~33%. Our source code and dataset are available at https://github.com/nguyenvo09/CombatingFakeNews.
arXiv commentSIGIR 2018
References in corpus (4)
Cited by in corpus (7)
- A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities
- The State of Human-centered NLP Technology for Fact-checking
- Crowdsourced Fact-Checking at Twitter: How Does the Crowd Compare With Experts?
- "This is Fake! Shared it by Mistake": Assessing the Intent of Fake News Spreaders
- Learning from Fact-checkers: Analysis and Generation of Fact-checking Language
- Suspicious News Detection Using Micro Blog Text
- Towards Reliable Online Clickbait Video Detection: A Content-Agnostic Approach