Detecting fake-review buyers using network structure: Direct evidence from Amazon.

ABSTRACT: Online reviews significantly impact consumers' decision-making process and firms' economic outcomes and are widely seen as crucial to the success of online markets. Firms, therefore, have a strong incentive to manipulate ratings using fake reviews. This presents a problem that academic researchers have tried to solve for over two decades and on which platforms expend a large amount of resources. Nevertheless, the prevalence of fake reviews is arguably higher than ever. To combat this, we collect a dataset of reviews for thousands of Amazon products and develop a general and highly accurate method for detecting fake reviews. A unique difference between previous datasets and ours is that we directly observe which sellers buy fake reviews. Thus, while prior research has trained models using l

SUBMITTER: He S 

PROVIDER: S-EPMC9704690 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature