基于情感分析的电商平台评论应用研究  

Research on the Application of E-commerce Platform Reviews Based on Sentiment Analysis

作　　者：鲁程逸 代子正 王艳红[1] Lu Chengyi;Dai Zizheng;Wang Yanhong(Evergrande School of Management,Wuhan University of Science and Technology,Wuhan430065,China)

机构地区：[1]武汉科技大学恒大管理学院,湖北武汉430065

出　　处：《科技创业月刊》2023年第10期150-154,共5页Journal of Entrepreneurship in Science & Technology

基　　金：湖北省省级大学生创新创业训练计划项目(S202210488096)。

摘　　要：传统的商品推荐算法忽略了消费者购买商品后的感受,而消费者在购物过程中更倾向于参考其他买家的意见,因此提出了基于情感分析的商品推荐算法,并应用于电商平台中。使用爬虫等技术获取电商平台用户评论信息,采用Word2vec技术制作适用于网络商品评论语言环境的情感词典,实现了一个基于淘宝的商品评论的推荐系统,并研究了评论有用性的方法框架,包括电商平台的评论信息获取、情感词典的制作、情感分析模型的搭建、分析结果的展示等方面。研究意义在于;针对用户评论的情感分析推荐算法仍处于探索阶段这一情况,提供了一种新的思路,并在实践中取得了一定的成果。Traditional product recommendation algorithms overlook the feelings of consumers after purchasing goods,while consumers are more inclined to refer to the opinions of other buyers during the shopping process.Therefore,a sentiment analysis-based product recommendation algorithm is proposed and applied to e-commerce platforms.User review information on e-commerce platforms was obtained using techniques such as web crawling.A sentiment dictionary suitable for the language environment of network product reviews was created using word2vec technology,and a recommendation system for product reviews based on Taobao was implemented.The research framework for analyzing the usefulness of reviews was analyzed,including aspects such as obtaining review information from e-commerce platforms,creating a sentiment dictionary,building a sentiment analysis model,and presenting analysis results.The significance of the research is that sentiment analysis-based recommendation algorithms for user reviews are still in the exploratory stage,and this research provides a new approach and has achieved certain results in practice.

关 键 词：电商平台 情感分析 推荐系统 网络用户评论 商品推荐算法 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]