Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake News

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pages 7717–7731, November 16–20, 2020. c⃝2020 Association for Computational Linguistics 7717 Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake News Nguyen Vo and Kyumin Lee Computer Science Department, Worcester Polytechnic Institute Worcester, Massachusetts, 01609, USA {nkvo,kmlee}@wpi.edu Abstract Although many fact-checking systems have been developed in academia and industry, fake news is still proliferating on social media. These systems mostly focus on fact-checking but usually neglect online users who are the main drivers of the spread of misinformation. How can we use fact-checked information to improve users’ consciousness of fake news to which they are exposed? How can we stop users from spreading fake news? To tackle these questions, we propose a novel framework to search for fact-checking arti- cles, which address the content of an origi- nal tweet (that may contain misinformation) posted by online users. The search can directly warn fake news posters and online users (e.g. the posters’ followers) about misinformation, discourage them from spreading fake news, and scale up verified content on social media. Our framework uses both text and images to search for fact-checking articles, and achieves promising results on real-world datasets. Our code and datasets are released at https:// github.com/nguyenvo09/EMNLP2020. 1 Introduction The rampant spread of biased news, partisan stories, false claims and misleading information has raised heightened societal concerns in recent years. Many reports pointed out that fabricated stories possibly caused citizens’ misperception about political can- didates (Allcott and Gentzkow, 2017), manipulated stock prices (Kogan et al., 2019) and threatened public health (Ashoka, 2020; Alluri, 2019). The proliferation of misinformation has pro- voked the rise of fact-checking systems worldwide. Since 2014, the number of fact-checking outlets has totally increased 400% in 60 countries (Stencel, 2019). However, fabricated stories and hoaxes are still pervading our cyberspace. Fig. 1 shows an example of a fake quote related to Barack Obama. carol Keep your promise Barack 28.1K Retweets 29K Likes November 09, 2016 2:53 AM FACT-CHECKED: President Obama Confirms He Will … President Obama has announced he'll refuse to leave … Snopes.com Text & Images of an original tweet Mock-up Figure 1: An original tweet and a mock-up of how a correctly retrieved fact-checking article is presented. The quote had been debunked by Snopes (Emery, 2016) on September 08, 2016 but two months later, it appeared again inside an original tweet posted by a Twitter user (called an original poster) and was retweeted over 28 thousand times. Perhaps, the original poster and people who shared the orig- inal tweet did not know if it was fact-checked or they might share it simply because it was suit- able for their personal preferences or ideologies (Lewandowsky et al., 2012). In other words, exist- ing fact-checking systems mainly focus on detec- tion but neglect online users who play the critical role in spreading fake news. After detecting fake news, what are the next steps to discourage people from sharing it? Recent studies …

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