Earticle

초록

영어

Online reviews offer valuable information to businesses by reflecting consumer experiences about their products and services. Two crucial aspects of online reviews are the topics consumers choose to address, and the sentiments expressed in their reviews. Building upon previous literature that shows online reviews are context- dependent, we employ the Expectation-Confirmation Theory (ECT) to examine the impact of topic distribution on review sentiment in South Korea and the U.S. during pre- and post-pandemic periods. After applying a topic modeling to Airbnb app review data, we measure the contribution of each topic on review sentiment using SHAP values. Our results indicate variations in topic distribution trends between 2018 and 2021. In addition, the order and magnitude of topics’ impact on review sentiment change between pre- and post-pandemic periods for both countries. This study can help businesses understand how topics and sentiments associated with their products and services changed after the pandemic and thus identify areas of improvement.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Literature Review
2.1. User Generated Content
2.2. Topic Modeling
2.3. Sentiment Analysis
Ⅲ. Theoretical Framework and Hypotheses Development
Ⅳ. Research Method
4.1. Data Collection
4.2. Research Framework
Ⅴ. Results
5.1. Topic Modeling and Topic Trends
5.2. Sentiment Analysis
5.3. Impact of Topic Distribution on Sentiment
Ⅵ. Conclusion

저자

• Mina Cho [ Graduate Student, Graduate School of Business, Seoul National University, Korea ]
• Dugmee Hwang [ Graduate Student, Graduate School of Business, Seoul National University, Korea ]
• SeongMin Jeon [ Associate Professor, College of Business, Gachon University, Korea ] Corresponding Author

참고문헌