Satire vs fake news: You can tell by the way they say it
In recent times, 'fake news' has become an increasingly important concept. Primarily, because information is now able to more quickly and deeply propagate among users due to the pervasive nature of the Internet and digital media. For this reason, it has recently received a large amount of attention from computer science researchers. A large number of studies demonstrate methods for detecting misinformation in content shared on the Internet. On the other hand, satire and irony as a part of usual human communication have received less attention. Whereas, fake news means misinformation meant to deceive people, satire is misinformation meant to entertain or criticize. Thus, despite both satire and fake news being misinformation these two concepts have different objectives and impacts. Currently, few studies have focused on differentiating between satire and fake news. In this paper, we present the limitations of existing works for classifying satire and fake news; discuss the feasibility of using a subjective concept like storytelling as a way to classify satire and fake news; and present a supervised learning approach to classify satire and fake news.
Fake news, Ibm watson, Narrative trajectory, Satire
Das, Dipto, and Anthony J. Clark. "Satire vs Fake News: You Can Tell by the Way They Say It." In 2019 First International Conference on Transdisciplinary AI (TransAI), pp. 22-26. IEEE, 2019.