Fact vs. Opinion: the Role of Argumentation Features in News Classification

Abstract

A 2018 study led by the Media Insight Project showed that most journalists think that a clear marking of what is news reporting and what is commentary or opinion (e.g., editorial, op-ed) is essential for gaining public trust. We present an approach to classify news articles into news stories (i.e., reporting of factual information) and opinion pieces using models that aim to supplement the article content representation with argumentation features. Our hypothesis is that the nature of argumentative discourse is important in distinguishing between news stories and opinion articles. We show that argumentation features outperform linguistic features used previously and improve on fine-tuned transformer-based models when tested on data from publishers unseen in training. Automatically flagging opinion pieces vs. news stories can aid applications such as fact-checking or event extraction.