Explainable Artificial Intelligence-Based Competitive Factor Identification

Juhee Han, Younghoon Lee

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Competitor analysis is an essential component of corporate strategy, providing both offensive and defensive strategic contexts to identify opportunities and threats. The rapid development of social media has recently led to several methodologies and frameworks facilitating competitor analysis through online reviews. Existing studies only focused on detecting comparative sentences in review comments or utilized low-performance models. However, this study proposes a novel approach to identifying the competitive factors using a recent explainable artificial intelligence approach at the comprehensive product feature level. We establish a model to classify the review comments for each corresponding product and evaluate the relevance of each keyword in such comments during the classification process. We then extract and prioritize the keywords and determine their competitiveness based on relevance. Our experiment results show that the proposed method can effectively extract the competitive factors both qualitatively and quantitatively.

Original languageEnglish
Article number3451529
JournalACM Transactions on Knowledge Discovery from Data
Volume16
Issue number1
DOIs
StatePublished - Jul 2021

Keywords

  • LRP
  • XAI
  • competitive factors
  • competitor analysis
  • mobile

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