Check-It: A plugin for detecting fake news on the web

Paschalides, Demetris Christodoulou Chrysovalantis Orphanou Kalia Andreou Rafael Kornilakis Alexandros Pallis George Dikaiakos Marios D.; Markatos, Evangelos

The rapid proliferation of misinformation and disinformation on the Internet has brought dire consequences upon societies around the world, fostering extremism, undermining social cohesion and threatening the democratic process. This impact can be attested by recent events like the COVID-19 pandemic and the 2020 US presidential election. The impact of misinformation has been so deep and wide that several authors characterize the present historic period as the “post-truth” era. Many recent efforts seek to contain the proliferation of misinformation by automating the identification of fake news through various techniques that exploit signals derived from linguistic processing of online content, analysis of message diffusion patterns, reputation lists, etc. In this paper we describe the design, implementation of, and experimentation with Check-It, a lightweight, privacy preserving browser plugin that detects fake-news. Check-It combines knowledge extracted from a variety of signals, and outperforms state-of-the-art methods on commonly-used datasets, achieving more than 90% accuracy, as well as a smooth user experience.