  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%.
