%0 Journal Article
%T 基于Apriori算法的国货彩妆产品在线评论数据关联分析<br>Correlation Analysis of Online Review Data of Domestic Makeup Products Based on Apriori Algorithm
%A 李颖
%J Advances in Applied Mathematics
%P 5562-5568
%@ 2324-8009
%D 2022
%I Hans Publishing
%R 10.12677/AAM.2022.118586
%X 本文旨在分析以完美日记为代表的国货品牌的在线评论，得出消费者重点关注的内容，以及评价内容中可能存在的关联规则，从而进一步推动国货彩妆品牌向国际品牌的发展。首先通过webscraper获取某网购平台上该品牌口红的相关评价数据。其次利用SPSS Modeler分析工具，通过Apriori算法对整理好的数据进行关联分析，得出研究结论。研究结果表明：现阶段由于信息渠道增多，电子商务提供的客服服务重要性下降；产品的价格、品牌、视觉评价、外包装都会影响消费者的购买评论；产品视觉评价受到多方面因素影响，包括产品内外包装、品牌力、嗅觉评价、触觉评价、价格和触觉的综合评价。品牌商可以借鉴消费者在线评论中的关联内容，通过改进相关产品属性或服务，进一步提升消费者对产品视觉上的评价，进而提升整体消费者满意度。<br />
This article aims to analyze the online reviews of domestic brands represented by Perfect Diary, draw the content that consumers pay attention to, and the possible correlation rules in the evalua-tion content, so as to further promote the development of domestic makeup brands to international brands. First of all, through webscraper, the relevant evaluation data of the brand lipstick on an online shopping platform was obtained. Secondly, using the SPSS Modeler analysis tool, the correla-tion analysis of the sorted data is carried out by the Apriori algorithm to draw the research conclu-sions. The results show that at this stage, due to the increase in information channels, the im-portance of customer service services provided by e-commerce has decreased; The price, brand, visual evaluation, and outer packaging of the product will all affect the consumer's purchase review; product visual evaluation is affected by many factors, including product internal and external packaging, brand power, olfactory evaluation, haptic evaluation, price and comprehensive evalua-tion of touch. Brands can learn from the relevant content in consumer online reviews to further en-hance consumer visual evaluation of products by improving relevant product attributes or services, thereby improving overall consumer satisfaction.
%K 在线评论，国货彩妆品牌，关联分析，网页爬虫，Apriori算法<br>Online Reviews
%K Domestic Makeup Brands
%K Association Analysis
%K Webscraper
%K Apriori Algorithm
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=54675