The Detection of Fake Reviews in Bestselling Books: Exploration and Findings

Kavita Krishnan and Yun Wan
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Kavita Krishnan: University of Houston-Victoria, USA
Yun Wan: University of Houston-Victoria, USA

Journal of Electronic Commerce in Organizations (JECO), 2021, vol. 19, issue 4, 64-79

Abstract: This study detected the possible manipulation of reviews for bestseller books. The authors first used clustering analysis to identify the cluster of bestselling books and patterns of manipulated reviews and ratings. They then used an artificial neural network to predict the possibility of review manipulation in bestselling books based on the patterns identified. The prediction outcome has an accuracy rate of 89%. They found that fake or manipulated reviews for bestselling books could be identified by analyzing abnormal rating fluctuations. The findings could help e-commerce platforms identify review manipulations and thereby help customers make prudent purchase decisions.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jeco00:v:19:y:2021:i:4:p:64-79

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