A Bayesian model of how people search online consumer reviews

Stelios Lelis, Andrew Howes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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Abstract

In this paper we describe a model of how people search online consumer reviews in service of purchasing decisions. The model is similar to other recent models of information seeking in that it updates estimates of products’ utilities using Bayesian inference. It is different, in that it stops seeking further information when the confidence that one of the alternatives is the best exceeds a threshold. Findings from a controlled experiment support the model by suggesting that high variance in review ratings causes people to seek more information.
Original languageEnglish
Title of host publicationProceedings of the 30th Annual Meeting of the Cognitive Science Society
PublisherCognitive Science Society
Pages553-558
Number of pages6
ISBN (Print)978-0-9768318-4-6
Publication statusPublished - 2008
EventCogSci 2008 - Washington, DC, USA
Duration: 23 Jul 200826 Oct 2008

Conference

ConferenceCogSci 2008
CityWashington, DC, USA
Period23/07/0826/10/08

Keywords

  • Information search
  • online consumer reviews
  • user modeling
  • threshold models

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