Vehicle defect discovery from social media

Alan S. Abrahams, Jian Jiao, G. Alan Wang, Weiguo Fan

Research output: Contribution to journalArticle

Abstract

A pressing need of vehicle quality management professionals is decision support for the vehicle defect discovery and classification process. In this paper, we employ text mining on a popular social medium used by vehicle enthusiasts: online discussion forums. We find that sentiment analysis, a conventional technique for consumer complaint detection, is insufficient for finding, categorizing, and prioritizing vehicle defects discussed in online forums, and we describe and evaluate a new process and decision support system for automotive defect identification and prioritization. Our findings provide managerial insights into how social media analytics can improve automotive quality management.

Original languageEnglish (US)
Pages (from-to)87-97
Number of pages11
JournalDecision Support Systems
Volume54
Issue number1
DOIs
StatePublished - Dec 1 2012
Externally publishedYes

Keywords

  • Business intelligence
  • Quality management
  • Social media analytics
  • Text mining

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Information Systems and Management

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  • Cite this

    Abrahams, A. S., Jiao, J., Wang, G. A., & Fan, W. (2012). Vehicle defect discovery from social media. Decision Support Systems, 54(1), 87-97. https://doi.org/10.1016/j.dss.2012.04.005