Zero-Shot Complaint Classification and Style-Controlled Response Generation via Large Language Models for Emotion-Aware E-Commerce Review Management
Abstract
We developed a large language model-powered system that classifies complaint categories and adapts response styles for e-commerce reviews. By integrating sentiment clustering, zero-shot classification, and style-conditioned prompt engineering, it enables context-aware, emotionally aligned reply generation for enhancing automated customer interaction and reputation management.
Fields of Study & Subjects
Sentiment Analysis and Opinion Mining
Topic Modeling
AI in Service Interactions
Publication details
- Pages
- 29–29
- Publication date
- 2 February 2026
- Language
- EN