Earticle

초록

영어

Customer reviews regarding services or products on the Internet have given both opportunities and challenges simultaneously to management. This study focuses on collecting those reviews online, discovering service complaints of customers, and tracking them over time. Along with two machine learning techniques such as sentiment analysis and structural topic modeling, this study effectively mines textual information to derive service complaints and to categorize potential service topics from the negative reviews. This study also traces the moving trends of the topics over time and reveals three major patterns emerged: rising, falling, and fluctuating. This research framework leverages a longitudinal analysis which can provide enriched insights regarding services or products to management.

목차

Abstract
 Introduction
 Related studies
 Methods
 Analysis results
 Conclusions
 References

저자

• KyungBae Park [ School of Business Administration, Kyungpook National University Daegu, Korea ]
• Sung Ho Ha [ School of Business Administration, Kyungpook National University Daegu, Korea ]

참고문헌