Abstract
Today, with so much free information online, it becomes increasingly difficult to make sense of what content is based on fact, half-truths or lies. Furthermore, in accordance with the events (e.g., COVID-19) that are increasingly alarming, the speed of false news spread is unprecedented. Of course, fake news impairs social stability and public trust, which calls for increasing demand for their detection. How to spot as faithful as possible fake news? The response that this article gives, by exploring the textual features using artificial intelligence and machine learning. This research addresses the problem of automatic fake news detection for Romanian language. First, we present a new corpus for automatic fake news detection that contains two subsets of 977 and 29 154 news articles in Romanian, separated according to labelling and collection methods. Second, we explore several text-based approaches for automatic fake news detection by using machine learning and artificial intelligence which resulted in an accuracy of 93%.
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