Calling out fake online reviews through robust epistemic belief

Snehasish Banerjee; Alton Y.K. Chua

doi:10.1016/j.im.2021.103445

Calling out fake online reviews through robust epistemic belief

Snehasish Banerjee^*, Alton Y.K. Chua

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

37 Citations (Scopus)

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
Journal	Information and Management
Volume	58
Issue number	3
DOIs	https://doi.org/10.1016/j.im.2021.103445
Publication status	Published - Apr 2021
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2021 Elsevier B.V.

ASJC Scopus Subject Areas

Management Information Systems
Information Systems
Information Systems and Management

Keywords

Authenticity
e-tourism
Epistemic belief
Fake review
Information processing
Online review

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10.1016/j.im.2021.103445

Cite this

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title = "Calling out fake online reviews through robust epistemic belief",

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.",

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AB - 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.

KW - Authenticity

KW - e-tourism

KW - Epistemic belief

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KW - Information processing

KW - Online review

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ER -

Calling out fake online reviews through robust epistemic belief

Abstract

Bibliographical note

ASJC Scopus Subject Areas

Keywords

Access to Document

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