Exploiting shopping and reviewing behavior to re-score online evaluations

Rong Zhang, Chao Feng Sha, Minqi Zhou, Aoying Zhou

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

12 Scopus citations

Abstract

Analysis to product reviews has attracted great attention from both academia and industry. Generally the evaluation scores of reviews are used to generate the average scores of products and shops for future potential users. However, in the real world, there is the inconsistency problem between the evaluation scores and review content, and some customers do not give out fair reviews. In this work, we focus on detecting the credibility of customers by analyzing online shopping and review behaviors, and then we re-score the reviews for products and shops. In the end, we evaluate our algorithm based on the real data set from Taobao, the biggest E-commerce site in China. Copyright is held by the author/owner(s).

Original languageEnglish
Title of host publicationWWW'12 - Proceedings of the 21st Annual Conference on World Wide Web Companion
Pages649-650
Number of pages2
DOIs
StatePublished - 2012
Event21st Annual Conference on World Wide Web, WWW'12 - Lyon, France
Duration: 16 Apr 201220 Apr 2012

Publication series

NameWWW'12 - Proceedings of the 21st Annual Conference on World Wide Web Companion

Conference

Conference21st Annual Conference on World Wide Web, WWW'12
Country/TerritoryFrance
CityLyon
Period16/04/1220/04/12

Keywords

  • Customer credibility
  • Review inconsistency

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