Check-It: A Plugin for Detecting and Reducing the Spread of Fake News and Misinformation on the Web
This addresses the spread of misinformation affecting web users, though it appears incremental as it builds on existing methods by integrating signals.
The authors tackled the problem of fake news and misinformation on the web by developing Check-It, a browser plugin that combines multiple signals for detection, achieving over 99% classification accuracy on a dataset of 9 million articles.
Over the past few years, we have been witnessing the rise of misinformation on the Web. People fall victims of fake news during their daily lives and assist their further propagation knowingly and inadvertently. There have been many initiatives that are trying to mitigate the damage caused by fake news, focusing on signals from either domain flag-lists, online social networks or artificial intelligence. In this work, we present Check-It, a system that combines, in an intelligent way, a variety of signals into a pipeline for fake news identification. Check-It is developed as a web browser plugin with the objective of efficient and timely fake news detection, respecting the user's privacy. Experimental results show that Check-It is able to outperform the state-of-the-art methods. On a dataset, consisting of 9 millions of articles labeled as fake and real, Check-It obtains classification accuracies that exceed 99%.