Calling out fake online reviews through robust epistemic belief

Snehasish Banerjee, Alton Y.K. Chua

Research output: Contribution to journalArticlepeer-review


Research shows that computational algorithms can classify online reviews as authentic or fake based on linguistic nuances. This study examines whether Internet users can process reviews in an algorithmic manner to discern authenticity. It also considers the role of epistemic belief—the individual trait that inherently determines one’s ability to separate fact from falsehood. In an online survey, 380 participants were each exposed to three hotel reviews—some authentic, others fake. Perceived specificity was positively related to perceived review authenticity, whereas perceived exaggeration showed a negative association. Epistemic belief with respect to justification for knowing significantly moderated both the relationships.
Original languageEnglish
Article number103445
Pages (from-to)1-13
Number of pages13
JournalInformation & management
Issue number3
Early online date10 Feb 2021
Publication statusE-pub ahead of print - 10 Feb 2021

Bibliographical note

© 2021 Elsevier B.V. All rights reserved. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy.


  • authenticity
  • e-tourism
  • information processing
  • Online review
  • fake review
  • Epistemic belief

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