Using text mining to analyze user forums

Ronen Feldman, Moshe Fresko, Jacob Goldenberg, Oded Netzer, Lyle Ungar

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

14 Scopus citations

Abstract

Product discussion boards are a rich source of information about consumer sentiment about products, which is being increasingly exploited. Most sentiment analysis has looked at single products in isolation, but users often compare different products, stating which they like better and why. We present a set of techniques for analyzing how consumers view product markets. Specifically, we extracted relative sentiment analysis and comparisons between products, to understand what attributes users compare products on, and which products they prefer on each dimension. We illustrate these methods in an extended case study analyzing the sedan car markets.

Original languageEnglish
Title of host publication5th International Conference Service Systems and Service Management - Exploring Service Dynamics with Science and Innovative Technology, ICSSSM'08
DOIs
StatePublished - 2008
Externally publishedYes
Event5th International Conference on Service Systems and Service Management, ICSSSM'08 - Melbourne, Australia
Duration: 30 Jun 20082 Jul 2008

Publication series

Name5th International Conference Service Systems and Service Management - Exploring Service Dynamics with Science and Innovative Technology, ICSSSM'08

Conference

Conference5th International Conference on Service Systems and Service Management, ICSSSM'08
Country/TerritoryAustralia
CityMelbourne
Period30/06/082/07/08

Keywords

  • Artificial intelligence
  • Information retrieval
  • Text mining
  • Unsupervised learning

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