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【6月25日】【互联网与数字经济系列讲座】Likely to be Real Unless It is Positive: Truth Bias, Veracity Effects, and the Role of Valence in Perceptions of Online Reviews

2024-06-12 10:35      


主讲人: 尹德志 副教授 (终身)


尹德志(Dezhi Yin),南佛罗里达大学穆马商学院,信息系统与管理系副教授(终身),博士生导师。2012年获得佐治亚理工学院大学博士学位,主要研究方向包括: 虚拟 AI 代理、嵌入式AI 和用户生成内容,在UTD24FT-50国际著名期刊的 Information Systems ResearchMIS QuarterlyProduction and Operations Management等发表高质量论文10多篇,连续多年在信息管理领域的重要刊物和会议担任匿名审稿专家。2022年获得Pre-ICIS研究研讨会最佳论文二等奖,2021年的INFORMS信息系统协会(ISS)获得Sandra A. Slaughter Early Career奖,2021年获工业与组织心理学学会William A. Owens Scholarly Achievement Award2021年获Information Systems Research 期刊的最佳审稿人奖,2017MIS Quarterly 期刊的年度杰出审稿人奖。




讲座题目《Likely to be Real Unless It is Positive: Truth Bias, Veracity Effects, and the Role of Valence in Perceptions of Online Reviews 》,co-authors: Dezhi Yin, Samuel D. Bond, and Han Zhang.


讲座摘要: In contrast to a growing stream of research in IS and related fields on the automated detection of “fake” online reviews, little is known about whether and why consumers trust reviews of unknown veracity. We explore the extent to which consumers perceive reviews as real (versus fake), the accuracy of those perceptions, and how they are influenced by review valence. Integrating literature on truth-default theory and deception motives, we propose that consumers have a general tendency to view reviews as real rather than fake (a truth bias) and are more accurate at detecting real reviews than fake reviews (a veracity effect), but that the truth bias and veracity effect are weaker for positive reviews than negative reviews. To test our hypotheses, we conducted five experiments in which participants were shown a set of reviews and classified each review as real or fake. The results supported our theorizing and identified the perception of deception motives as an important process mechanism. Our findings offer important implications for firms and review platforms as they establish priorities for combating fake reviews.


时间:2024年6月25日上午9:30-11:30


地点:学院南路校区主教105研讨室


近期发表的UT Dallas- 24、FT-50期刊论文如下:

1)Han E, Yin D, Zhang H. Bots with Feelings: Should AI Agents Express Positive Emotion in Customer Service? [J]. Information Systems Research, 2022.

2)Jiang L, Yin D, Liu D, et al. The More Enthusiastic, the Better? Unveiling a Negative Pathway From Entrepreneurs’ Displayed Enthusiasm to Funders’ Funding Intentions[J]. Entrepreneurship Theory and Practice, 2022: 10422587221076391.

3)Yin D, de Vreede T, M. Steele L, et al. Decide Now or Later: Making Sense of Incoherence Across Online Reviews[J]. Information Systems Research, 2022.

4)Lei Z, Yin D, Mitra S, et al. Swayed by the reviews: Disentangling the effects of average ratings and individual reviews in online word‐of‐mouth[J]. Production and Operations Management, 2022, 31(6): 2393-2411.

5)Lei Z, Yin D, Zhang H. Focus within or on others: The impact of reviewers’ attentional focus on review helpfulness[J]. Information Systems Research, 2021, 32(3): 801-819.

6)Yin D, Bond S, Zhang H. Anger in consumer reviews: Unhelpful but persuasive? [J]. MIS Quarterly, Forthcoming, Georgia Tech Scheller College of Business Research Paper, 2020 (3588859).

(7)Peng C H, Yin D, Zhang H. More than words in medical question-and-answer sites: a content-context congruence perspective[J]. Information systems research, 2020, 31(3): 913-928.

8)Jiang L, Yin D, Liu D. Can joy buy you money? The impact of the strength, duration, and phases of an entrepreneur’s peak displayed joy on funding performance[J]. Academy of Management Journal, 2019, 62(6): 1848-1871.


主办中国互联网经济研究院


此次讲座获“高等学校学科创新引智基地资助”(Supported by the 111 Center)(B20094),特此致谢。


撰稿:王天梅      排版:张思域

初审孙宝文      复审王立勇