Toward a theoretical model of authentic and fake user-generated online reviews

Snehasish Banerjee, Alton Y.K. Chua

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review


As consumers increasingly rely on user-generated online reviews to make purchase decisions, the prevalence of fake entries camouflaged among authentic ones has become a growing concern. On the scholarly front, this has given rise to two disparate research strands. The first focuses on ways to distinguish between authentic and fake reviews but ignores consumers’ perceptions. The second deals with consumers’ perceptions of reviews without delving into their ability to discern review authenticity in the first place. As a result of the fragmented literature, what has eluded scholarly attention is the extent to which consumers are able to perceive actual differences between authentic and fake reviews. To this end, the chapter highlights the theoretical value of weaving the two research strands together. With the aim to contribute to the theoretical discussion surrounding the problem, it specifically develops what is referred as the Theoretical model of Authentic and Fake reviews (the TAF). New research directions are identified based on the TAF.
Original languageEnglish
Title of host publicationHandbook of Research on Deception, Fake News, and Misinformation Online
PublisherHershey, PA: IGI Global
Number of pages17
Publication statusPublished - 2019


  • Authenticity
  • Deception
  • Linguistic cue
  • online review
  • opinion spam
  • social media
  • User-generated content
  • User perception

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