Calling out fake online reviews through robust epistemic belief

• Published in: Information & management 2021-04, Vol.58 (3), p.103445, Article 103445
• Main Authors: Banerjee, Snehasish, Chua, Alton Y.K.
• Format: Article
• Language: English
• Subjects: Authenticity; e-tourism; Epistemic belief; Fake review; Information processing; Online review
• ISSN: 0378-7206; 1872-7530
• DOI: 10.1016/j.im.2021.103445

•Linguistic cues help people discern online review authenticity to a certain extent.•Perceived exaggeration relates negatively to perceived hotel review authenticity.•Perceived specificity relates positively to perceived hotel review authenticity.•Epistemic belief (perceived justification for knowing) is a significant moderator.•Truth bias impedes people’s ability to ascertain authenticity of online reviews. 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.