Work of Piotr Przybyła was accepted at AAAI 2020
Work of Piotr Przybyła on automatic methods that can detect online documents of low credibility was accepted at AAAI 2020.
AAAI conference series is to promote research in artificial intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers in AI and its affiliated disciplines. AAAI-20 is the Thirty-Fourth AAAI Conference on Artificial Intelligence.
In this study we aim to explore automatic methods that can detect online documents of low credibility, especially fake news, based on the style they are written in. We show that general-purpose text classifiers, despite seemingly good performance when evaluated simplistically, in fact overfit to sources of documents in training data. In order to achieve a truly style-based prediction, we gather a corpus of 103,219 documents from 223 online sources labelled by media experts, devise realistic evaluation scenarios and design two new classifiers: a neural network and a model based on stylometric features. The evaluation shows that the proposed classifiers maintain high accuracy in case of documents on previously unseen topics (e.g. new events) and from previously unseen sources (e.g. emerging news websites). An analysis of the stylometric model indicates it indeed focuses on sensational and affective vocabulary, known to be typical for fake news.
