Activities per year
Abstract
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 language | English |
---|---|
Article number | 103445 |
Pages (from-to) | 1-13 |
Number of pages | 13 |
Journal | Information & management |
Volume | 58 |
Issue number | 3 |
Early online date | 10 Feb 2021 |
DOIs | |
Publication status | E-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.Keywords
- authenticity
- e-tourism
- information processing
- Online review
- fake review
- Epistemic belief
Activities
- 1 Media (Press)
-
How accurate are algorithms in detecting fake reviews online?
Banerjee, S. (Advisor)
11 Mar 2021Activity: Other › Media (Press)