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http://dx.doi.org/10.5859/KAIS.2017.26.4.327

Customer Service Evaluation based on Online Text Analytics: Sentiment Analysis and Structural Topic Modeling  

Park, KyungBae (School of Business Administration, Kyungpook National University)
Ha, Sung Ho (School of Business Administration, Kyungpook National University)
Publication Information
The Journal of Information Systems / v.26, no.4, 2017 , pp. 327-353 More about this Journal
Abstract
Purpose Social media such as social network services, online forums, and customer reviews have produced a plethora amount of information online. Yet, the information deluge has created both opportunities and challenges at the same time. This research particularly focuses on the challenges in order to discover and track the service defects over time derived by mining publicly available online customer reviews. Design/methodology/approach Synthesizing the streams of research from text analytics, we apply two stages of methods of sentiment analysis and structural topic model incorporating meta-information buried in review texts into the topics. Findings As a result, our study reveals that the research framework effectively leverages textual information to detect, prioritize, and categorize service defects by considering the moving trend over time. Our approach also highlights several implications theoretically and practically of how methods in computational linguistics can offer enriched insights by leveraging the online medium.
Keywords
Service Evaluation; Sentiment Analysis; Structural Topic Model; Text Mining;
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