Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake News
This addresses the issue of misinformation spread on social media for online users, though it is incremental as it builds on existing fact-checking systems.
The paper tackles the problem of fake news proliferation by proposing a framework that searches for fact-checking articles based on the content of tweets, aiming to warn users and discourage the spread of misinformation, achieving promising results on real-world datasets.
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 articles, which address the content of an original 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.