基于Django的陶瓷商品评论情感分析系统设计

Design of a Sentiment Analysis System for Ceramic Product Reviews Based on Django

摘要: 随着互联网的兴起，各大电商平台上的商品评价对消费者的购买决策产生了重大影响，特别是在购买文化和艺术价值较高的陶瓷商品时。为了帮助消费者和企业更好地利用和分析这些评论信息，本文设计并实现了一个基于Django框架的陶瓷商品评论情感分析系统，该系统通过数据挖掘技术和机器学习算法对消费者评论进行模型的训练和情感分析。系统后端使用Python进行开发，前端则利用Bootstrap和Pyechart等技术，实现了对分析结果的直观可视化展示，帮助消费者更全面地了解所要购买的商品。

Abstract: With the rise of the Internet, product reviews on various e-commerce platforms have significantly influenced consumer purchasing decisions, especially when buying ceramics with high cultural and artistic value. To assist consumers and businesses in better utilizing and analyzing these reviews, this paper designs and implements a sentiment analysis system for ceramic product reviews based on the Django framework. This system employs data mining techniques and machine learning algorithms to train models on consumer reviews and conduct sentiment analysis. The backend of the system is developed using Python, while the frontend utilizes technologies like Bootstrap and Pyechart to visually display the analysis results, helping consumers gain a comprehensive understanding of the products they intend to purchase.