基于文本挖掘的大疆无人机评论情感实证研究  

An Empirical Study on Emotional Analysis of Dajiang UAV Comments Based on Text Mining

作　　者：尚雨浩 陈涵怡 金婷婷 

机构地区：[1]南京信息工程大学数学与统计学院,江苏 南京

出　　处：《运筹与模糊学》2024年第1期279-292,共14页Operations Research and Fuzziology

摘　　要：充分利用好电商平台的文本评论语料,可以挖掘出商品和企业背后的优势和潜在价值。本文通过网络爬虫工具获取大疆无人机在京东商城的网购评论,在对评论语料进行文字预处理的基础上,通过传统的情感词典方法以及机器学习中的伯努利朴素贝叶斯、KNN、SVM对评论语料所含的情感倾向分类并评价。对大疆无人机商品建立LDA主题模型,计算余弦值距离确定最优主题数后更深一步挖掘评论的主题及关注点。发现消费者对于大疆无人机的质量、飞行操纵性、品牌效应、视频拍摄效果、物流配送和配套设施较为关注。最后依据文本挖掘的结果,分析大疆产品的优势,并为生厂商和客户分别提供相关建议。Making full use of the text comment corpus of e-commerce platform can explore the advantages and potential value behind commodities and enterprises. This paper obtains the online shopping comments of Dajiang UAV in Jingdong Mall through the web crawler tool. Based on the word preprocessing of the comment corpus, this paper classifies and evaluates the emotional orientation contained in the comment corpus through the traditional emotional dictionary method and Bernoulli Naive Bayes, KNN and SVM in machine learning. Establishing LDA theme model for Dajiang UAV products, calculateing the cosine distance to determine the optimal number of themes, and further explore the themes and concerns of comments. It is found that consumers pay more attention to the quality, flight maneuverability, brand effect, video shooting effect, express delivery and supporting facilities of Dajiang UAV. Finally, according to the results of text mining, this paper analyzes the advantages of Dajiang products, and provides relevant suggestions for manufacturers and customers respectively.

关 键 词：文本挖掘 情感倾向分析 机器学习 LDA主题模型 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]