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

TY - JOUR

T1 - Don’t be deceived

T2 - Using linguistic analysis to learn how to discern online review authenticity

AU - Banerjee, Snehasish

AU - Chua, Alton Y.K.

AU - Kim, Jung-Jae

N1 - © 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

PY - 2017/5/17

Y1 - 2017/5/17

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85018552707&partnerID=8YFLogxK

U2 - 10.1002/asi.23784

DO - 10.1002/asi.23784

M3 - Article

SN - 2330-1635

VL - 68

SP - 1525

EP - 1538

JO - Journal of the Association for Information Science and Technology

JF - Journal of the Association for Information Science and Technology

IS - 6

ER -