Online persuasion of review emotional intensity: A text mining analysis of restaurant reviews

被引：76
作者：
Li, Hengyun [1 ]
Liu, Hongbo [2 ]
Zhang, Zili [3 ]
机构：
[1] Hong Kong Polytech Univ, Sch Hotel & Tourism Management, Hong Kong, Peoples R China
[2] Univ Surrey, Sch Hospitality & Tourism Management, Guildford, Surrey, England
[3] Harbin Inst Technol, Sch Management, 92 West Dazhi St, Harbin, Peoples R China
来源：
INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT | 2020年 / 89卷
基金：
中国国家自然科学基金;
关键词：
Emotional intensity; Discrete emotion; Review usefulness; Review length; Reviewer expertise; HOTEL REVIEWS; DISCRETE EMOTIONS; NEGATIVITY BIAS; PERCEIVED HELPFULNESS; CONSUMER REVIEWS; AROUSAL; IMPACT; DOMINANCE; ATTENTION; RESPONSES;
D O I：
10.1016/j.ijhm.2020.102558
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
Consumer-generated restaurant reviews are important sources in consumers' purchase decisions. The purpose of this study is to explore the impact of emotional intensity on perceived review usefulness as well as the moderating effects of review length and reviewer expertise. Data from 600,686 reviews of 300 popular restaurants in the US were obtained from Yelp. Using a text mining approach and econometric analysis, empirical results show that (1) positive emotional intensity has a negative impact on perceived review usefulness, whereas negative emotional intensity has a positive impact on perceived review usefulness; (2) among the two most prevalent discrete negative emotions in online reviews (i.e., anger and anxiety), reviews expressing anger are more useful than those expressing anxiety; and (3) review length and reviewer expertise can moderate the effect of emotional intensity on perceived review usefulness.
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收藏
页数：13
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