earticle

영어

This study employs text mining techniques to analyze online customer reviews, focusing on two product categories—hedonic and utilitarian—as well as corresponding seller responses. Using sentiment analysis and Latent Dirichlet Allocation (LDA) topic modeling, the research identifies key themes in negative reviews, revealing the specific aspects of the purchasing experience that consumers emphasize when expressing dissatisfaction. Furthermore, the study examines seller response patterns to assess the effectiveness of various response strategies in mitigating the impact of negative feedback. Results show that Consumer concerns vary by product type: buyers of utilitarian products primarily highlight functional failures, whereas buyers of hedonic products tend to focus on emotional dissatisfaction. These findings offer insights into businesses, contributing to a deeper understanding of consumer behavior in the face of negative reviews. The results can inform the development of more effective crisis management strategies and optimized response mechanisms, enhancing consumer trust and encouraging repurchase intentions.