The ebb and flow of online word of mouth

Zhihong Ke, De Liu, Alok Gupta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The robustness of online reviews is an important but understudied issue. One way to approach this issue is to study how potential reviewers react to an observable aberration in aggregate ratings. We design two studies - an econometric analysis using archived Yelp data, and a randomized online experiment - to systematically examine the relationship between aberrations in aggregate ratings and volume and valence of subsequent reviews. Two studies consistently demonstrate an ebb and flow pattern of online WOM. Specifically, a positive aberration leads to a negative correction (rating down), and a negative aberration leads to a positive correction (rating up). On the other hand, we find mixed effects on volume of new reviews: the experiment suggests that a positive rating aberration boosts volume of reviews while a negative one reduces it; the observational data analysis shows a slight volume boosting effect by negative rating aberrations.

Original languageEnglish (US)
Title of host publication2016 International Conference on Information Systems, ICIS 2016
PublisherAssociation for Information Systems
ISBN (Electronic)9780996683135
StatePublished - Jan 1 2016
Event2016 International Conference on Information Systems, ICIS 2016 - Dublin, Ireland
Duration: Dec 11 2016Dec 14 2016

Publication series

Name2016 International Conference on Information Systems, ICIS 2016

Other

Other2016 International Conference on Information Systems, ICIS 2016
CountryIreland
CityDublin
Period12/11/1612/14/16

Keywords

  • Online reviews
  • Robustness
  • Valence
  • Volume
  • WOM

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