Social opinion mining for supporting buyers’ complex decision making: exploratory user study and algorithm comparison

Li CHEN*, Luole Qi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

This article reports our study of the role of social content (i.e., user-generated content in social networking environment) in online consumers’ decision process when they search for an inexperienced product to buy. Through close observation of users’ objective behavior and interview of their reflective thoughts during an initial exploratory user study, we have first derived a set of system implications and integrated these implications into a three-stage system architecture. Furthermore, driven by the specific implication regarding the impact of user reviews in influencing users’ decision stages, we have presented a linear-chain conditional random-field-based social-opinion-mining algorithm, and have identified its higher effectiveness against related algorithms in an experiment. Finally, we present our system’s user interfaces and emphasize on how to display the opinion-mining results in the form of both quantitative presentation and qualitative visualization.

Original languageEnglish
Pages (from-to)301-320
Number of pages20
JournalSocial Network Analysis and Mining
Volume1
Issue number4
DOIs
Publication statusPublished - 1 Jan 2011

Scopus Subject Areas

  • Information Systems
  • Communication
  • Media Technology
  • Human-Computer Interaction
  • Computer Science Applications

User-Defined Keywords

  • Complex decision making
  • Decision system
  • Inexperienced products
  • Opinion mining
  • Social content
  • Users’ information needs

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