Detecting fake news is becoming widely acknowledged as a critical activity with significant implications for social impact. As fake news tends to evoke high-activating emotions from audiences, the role of emotions in identifying fake news is still under-explored. Existing research made efforts in examining effective representations of emotions conveyed in the news content to help discern the veracity of the news. However, the aroused emotions from the audience are usually ignored. This paper first demonstrates effective representations of emotions within both news content and users’ comments. Furthermore, we propose an emotion-aware fake news detection framework that seamlessly incorporates emotion features to enhance the accuracy of identifying fake news. Future work will include thorough experiments to prove that the proposed framework with the emotions expressed in news and users’ comments improves fake news detection performance.
Xiao, Kenan Auburn University; Gupta, Ashish; Jiang, Wenting; and Qin, Xiao, "Exploring Roles of Emotion in Fake News Detection" (2021). Proceedings of the 2021 Pre-ICIS SIGDSA Symposium. 11.