Estimating deception in consumer reviews based on extreme terms: Comparison analysis of open vs. closed hotel reservation platforms

2019
We examine how open and closed review posting policies play differentiating roles in creating social media bias. As a supplementary method to existing ones detecting fake reviews, we develop a trust measure estimating how genuine the review is, based on the frequent usage of strongly positive or negative words. Using the hotel industry as our application context, we empirically demonstrate that our trust measure serves as a correction factor that reduces social media bias. Interestingly, we observe particular hotel service features revealing strong upward manipulation to promote the businesses (for example, positive overall recommendation, interesting surroundings, and personal travel). By contrast, we identify some other features that reveal the presence of strong downward manipulation (for example, negative overall recommendation, disappointing room amenities, and poor atmosphere). From a practical perspective, this research can help both managers and consumers make better informed decisions by reducing the impact attributable to social media manipulation.
JOURNAL OF BUSINESS RESEARCH
页码:83-96|卷号:102
ISSN:0148-2963
收录类型
SSCI
发表日期
2019
学科领域
循证经济学
国家
美国
语种
英语
DOI
10.1016/j.jbusres.2019.05.016
其他关键词
SOCIAL MEDIA; ANONYMITY; BEHAVIOR; QUALITY; IMPACT; FAKE; USER
EISSN
1873-7978
资助机构
Hankuk University of Foreign Studies Research Fund of 2019
资助信息
We also appreciate the support by Hankuk University of Foreign Studies Research Fund of 2019.
被引频次(WOS)
11
被引更新日期
2022-01
来源机构
University of North Carolina University of North Carolina Charlotte Hankuk University Foreign Studies University of North Carolina University of North Carolina Charlotte University of Western Australia
关键词
Online consumer reviews Social media manipulation Text analytics Hotel reviews