Don’t be deceived: Using linguistic analysis to learn how to discern online review authenticity

Snehasish Banerjee, Alton Y.K. Chua, Jung-Jae Kim

Research output: Contribution to journalArticlepeer-review


This article uses linguistic analysis to help users discern the authenticity of online reviews. Two related studies were conducted using hotel reviews as the test case for investigation. The first study analyzed 1,800 authentic and fictitious reviews based on the linguistic cues of comprehensibility, specificity, exaggeration, and negligence. The analysis involved classification algorithms followed by feature selection and statistical tests. A filtered set of variables that helped discern review authenticity was identified. The second study incorporated these variables to develop a guideline that aimed to inform humans how to distinguish between authentic and fictitious reviews. The guideline was used as an intervention in an experimental setup that involved 240 participants. The intervention improved human ability to identify fictitious reviews amid authentic ones.
Original languageEnglish
Pages (from-to)1525-1538
Number of pages14
JournalJournal of the Association for Information Science and Technology
Issue number6
Early online date20 Apr 2017
Publication statusPublished - 17 May 2017

Bibliographical note

© 2017 ASIS&T. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

Cite this