The good, the bad and the content: beyond negativity bias in online word-of-mouth

Emotion;Affect;Integrity;Competence;Electronic commerce;Trust;Information diagnosticity;Judgments and decision making;Negativity bias;User-generated content;Online reviews;Discrete emotions

Yin, Dezhi ; Management

University:Georgia Institute of Technology

Department:Management

关键词: Emotion;    Affect;    Integrity;    Competence;    Electronic commerce;    Trust;    Information diagnosticity;    Judgments and decision making;    Negativity bias;    User-generated content;    Online reviews;    Discrete emotions;   

Others  :  https://smartech.gatech.edu/bitstream/1853/44824/1/yin_dezhi_201208_phd.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

My dissertation aims to contribute to a more comprehensive understanding of how consumers make sense of online word-of-mouth. Each essay in my dissertation probes beyond the effect of rating valence and explores the role of textual content. In the first essay, I explore negativity bias among online consumers evaluating peer information about potential sellers. I propose that both the likelihood of negativity bias and resistance to change after a trust violation will depend on the domain of information discussed in a review. Three experiments showed that negativity bias is more prominent for information regarding sellers' integrity than information regarding their competence. These findings suggest that the universality of negativity bias in a seller review setting has been exaggerated.In the second essay, I examine the impact of emotional arousal on the perceived helpfulness of text reviews. I propose an inverse U-shaped relationship by which the arousal conveyed in a text review will be associated by readers with lower perceived helpfulness only beyond an optimal level, and that the detrimental effect of arousal is present for negative reviews even when objective review content is controlled for. To test these hypotheses, two studies were conducted in the context of Apple's mobile application market. In Study 1, I collected actual review data from Apple's App Store, coded those reviews for arousal using text analysis tools, and examined the non-linear relationship between arousal and review helpfulness. In Study 2, I experimentally manipulated the emotional arousal of reviews at moderate to high levels while holding objective content constant. Results were largely consistent with the hypotheses. This essay reveals the necessity of considering emotional arousal when evaluating review helpfulness, and the results carry important practical implications.In the third essay, I explore effects of the emotions embedded in a seller review on its perceived helpfulness to readers. I propose that over and above the well-known negativity bias, the impact of discrete emotions in a review will vary, and that one source of this variance is perceptions of reviewers' cognitive effort. I focus on the roles of two distinct, negative emotions common to seller reviews: anxiety and anger. In Studies 1 and 2, experimental methods were utilized to identify and explain the differential impact of anxiety and anger in terms of perceived reviewer effort. In Study 3, actual seller reviews from Yahoo! Shopping websites were collected to examine the relationship between emotional review content and helpfulness ratings. These findings demonstrate the importance of discriminating between discrete emotions in online word-of-mouth, and they have important repercussions for consumers and online retailers.