基于在线评论聚类的奶茶店顾客满意度研究

Rong Huang, Shuai Mao, Yin Chen
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引用次数: 0

摘要

互联网的普及使消费者更容易在网上发布自己的生活看法和日常生活,消费者也意识到网上的评论是一种有用的信息资源,可以影响他们的消费意愿。在本文中,我们使用后羿采集器进行数据挖掘,从2020年到2022年,我们收集了7000多条美团点评,然后通过SPSS对与顾客满意度相关的特征词进行K-means聚类分析,确定各奶茶店顾客关注的焦点,为商家提供可靠的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study of Customer Satisfaction in Milk Tea Stores Based on Online Comment Clustering
The popularity of the Internet has made it easier for consumers to post their life perceptions and daily routines on the Web, and consumers are aware that online comments are a useful information resource and can influence their consumption intentions. In this paper, we use the Houyi collector for data mining, from 2020 to 2022, more than 7000 comments from Meituan have been collected, and then K-means clustering analysis is performed on the feature words related to customer satisfaction through SPSS to determine the focus of customers of each milk tea store and provide reliable suggestions for merchants.
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