TY - JOUR
T1 - The Effect of the Expressed Anger and Sadness on Online News Believability
AU - Deng, Bingjie
AU - Chau, Michael
N1 - Funding Information:
We are extremely grateful to the guest editors and the anonymous reviewers for their invaluable comments and suggestions throughout the review process. We also thank all participants of the experiments.
Publisher Copyright:
© 2021 Taylor & Francis Group, LLC.
PY - 2021/12
Y1 - 2021/12
N2 - 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.
AB - 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.
KW - anger online
KW - appraisal-tendency framework
KW - discrete emotions
KW - emotions as social information theory
KW - fake news
KW - news perception
KW - online disinformation
KW - sadness online
KW - social media behavior
UR - http://www.scopus.com/inward/record.url?scp=85122203764&partnerID=8YFLogxK
U2 - 10.1080/07421222.2021.1990607
DO - 10.1080/07421222.2021.1990607
M3 - Article
AN - SCOPUS:85122203764
SN - 0742-1222
VL - 38
SP - 959
EP - 988
JO - Journal of Management Information Systems
JF - Journal of Management Information Systems
IS - 4
ER -