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논문검색

NMS(New Media Service)

Detecting Fake Reviews : Exploring the Linguistic Characteristics by Computerized Text Analysis

초록

영어

Online consumer reviews have become the most important basis for online shopping and product sales. Fake reviews are generated to boost sales because online consumer reviews play a vital role in consumers’ decision making. The prevalence of fake reviews violates the regulations of the online business environment and misleads consumers in decision making. Thus, the present research investigates the effects of reviews’ linguistic characteristics (i.e., analytical thinking, authenticity) on review fakeness. Specifically, this research examines whether (1) the level of analytical thinking is lower for fake (vs. genuine) reviews (hypothesis 1) and (2) the level of authenticity is lower for fake (vs. genuine) reviews (hypothesis 2). This research analyzed usergenerated hotel reviews (genuine reviews, fake reviews) collected from MTurk. Linguistic Inquiry and Word Count (LIWC) 2022 was adopted to code review contents, and the hypotheses were tested using logistic regression. Consistent with the hypotheses 1 and 2, the results indicate that (1) analyticial thinking is negatively associated with review fakeness; and (2) authenticity is negatively associated with review fakeness. The findings provide important implications to identify fake reviews based on linguistic characteristics.

목차

Abstract
1. Introduction
2. Theoretical Background and Hypotheses Development
2.1 Online Consumer Reviews and Computerized Text Analysis
2.2 Analytical Thinking
2.3 Authenticity
3. Method
3.1 Data Collection
3.2 Procedure and Measures
3.3 Data Analysis
4. Results
5. Conclusion
Acknowledgement
References

저자정보

  • Moon-Yong Kim Professor, College of Business, Hankuk University of Foreign Studies, Seoul, Korea

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