Bingjie Amber DENG
Ms. Bingjie Amber DENG
創新及資訊管理學
Research Postgraduate Student

3917 7735

Programme

4-year PhD

Field of Study

Innovation and Information Management

Research Interests
  • Fintech
  • Social Media
  • E-Commerce
  • Human-Computer Interaction (HCI)
Education
  • MEcon, The University of Hong Kong
  • BBA, Beijing Normal University-Hong Kong Baptist University-United International College
Recent Publications
The Effect of the Expressed Anger and Sadness on Online News Believability

Emotional expressions have been widely used in online news. Existing research on the perception of online news has primarily focused on the effect of contextual cues on readers’ reasoning and deliberation behavior; the role of discrete emotions such as anger and sadness, however, has been overlooked. This paper addresses this research gap by investigating the influence of angry and sad expressions in online news on readers’ perception of the news. Drawing on the emotions as social information (EASI) theory and the appraisal-tendency framework (ATF), we find that expressions of anger in online news decrease its believability. However, sad expressions do not trigger the same effect. A further test reveals that the effect of angry expressions can be explained by the readers’ perception of the author’s cognitive effort: readers perceive that expressions of anger in the headlines denote a lack of cognitive effort of the author in writing the news, which subsequently lowers the believability of the news. We also show that news believability has downstream implications and can impact various social media behaviors including reading, liking, commenting, and sharing. This research extends current knowledge of the cognitive appraisals and interpersonal effects of discrete emotions (i.e., anger, sadness) on online news. The results also offer practical implications for social media platforms, news aggregators, and regulators that need to manage digital content and control the spread of fake news.