当前位置: X-MOL 学术J. Manag. Info. Syst. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
The Effect of the Expressed Anger and Sadness on Online News Believability
Journal of Management Information Systems ( IF 7.7 ) Pub Date : 2022-01-02 , DOI: 10.1080/07421222.2021.1990607
Bingjie Deng 1 , Michael Chau 1
Affiliation  

ABSTRACT

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.



中文翻译:

表达愤怒和悲伤对在线新闻可信度的影响

摘要

情感表达在网络新闻中被广泛使用。现有关于网络新闻感知的研究主要集中在情境线索对读者推理和深思熟虑行为的影响上;然而,诸如愤怒和悲伤等离散情绪的作用却被忽视了。本文通过调查在线新闻中愤怒和悲伤的表达对读者对新闻感知的影响来填补这一研究空白。利用作为社会信息的情绪(EASI)理论和评价-倾向框架(ATF),我们发现在线新闻中的愤怒表达会降低其可信度。但是,悲伤的表情不会触发相同的效果。进一步的测试表明,愤怒表情的影响可以通过读者对作者认知努力的感知来解释:读者认为,标题中的愤怒表达表明作者在撰写新闻时缺乏认知努力,从而降低了新闻的可信度。我们还表明,新闻可信度具有下游影响,可以影响各种社交媒体行为,包括阅读、喜欢、评论和分享。这项研究扩展了当前关于离散情绪(即愤怒、悲伤)对在线新闻的认知评估和人际关系影响的知识。结果还为需要管理数字内容和控制假新闻传播的社交媒体平台、新闻聚合器和监管机构提供了实际意义。我们还表明,新闻可信度具有下游影响,可以影响各种社交媒体行为,包括阅读、喜欢、评论和分享。这项研究扩展了当前关于离散情绪(即愤怒、悲伤)对在线新闻的认知评估和人际关系影响的知识。结果还为需要管理数字内容和控制假新闻传播的社交媒体平台、新闻聚合器和监管机构提供了实际意义。我们还表明,新闻可信度具有下游影响,可以影响各种社交媒体行为,包括阅读、喜欢、评论和分享。这项研究扩展了当前关于离散情绪(即愤怒、悲伤)对在线新闻的认知评估和人际关系影响的知识。结果还为需要管理数字内容和控制假新闻传播的社交媒体平台、新闻聚合器和监管机构提供了实际意义。

更新日期:2022-01-03
down
wechat
bug