摘要
目的分析产品在线网络评论,准确评估用户的使用反馈和需求信息,用于产品改进设计。方法用网络爬虫采集购物网站的商品评论数据,引入百度AI开放平台的自然语言处理技术,对清洗后的评论数据进行情感分析,计算每条评论的情感极性,结合Nvivo文本分析和人工筛选,得到准确的用户评价。在质量功能展开(QFD)中,评论分析的结果用于产品的目标质量规划,根据质量屋得出的技术特性相对重要度,选择应重点改进的技术属性。结果该方法发现了产品需要改进的多个重要设计问题,以无线手持吸尘器为例,对比传统调研方法的分析结果,验证该方法的有效性。结论对网络评论大数据的AI情感分析结合QFD,能发现产品需要改进的大部分问题,具有重要的参考价值,能为产品改进设计提供新方法。
Online product reviews are analyzed to accurately assess user feedback and demand information for product improvement design.Using web crawler to collect online reviews of shopping websites.The natural language processing technology of Baidu AI open platform was introduced to conduct sentiment analysis on the comment data after cleaning,calculate the emotional polarity of each comment,and combines with the text analysis of Nvivo software and artificial selection to get accurate analysis of user comments.In quality function deployment(QFD),the results of online reviews analysis are used in the target quality planning of the product,and according to relative importance of technical attributes obtained from the house of quality,the technical attributes to be improved are selected.This method finds out several important design problems that need to be improved.Taking the wireless handheld vacuum cleaner as an example,the effectiveness of this method is verified by comparing the analysis results of traditional research methods.AI sentiment analysis of online reviews combined with QFD can find most of problems that need to be improved,which has important reference value and can provide new methods for product design improvement.
作者
王琴
刘毅
WANG Qin;LIU Yi(South China University of Technology,Guangzhou 510006,China;Guangdong Key Laboratory of Industrial Design Creativity and Application Research,Guangzhou 511442,China)
出处
《包装工程》
CAS
北大核心
2021年第24期169-174,共6页
Packaging Engineering
基金
广东省科技计划项目(2017B030314169)。
关键词
网络评论
情感分析
QFD
改进设计
online reviews
sentiment analysis
QFD
improvement design
