Word Cloud Analysis of Customer Satisfaction in Cosmetic Products in Thailand

O. Thinnukool, Phasit Charoenkwan, P. Khuwuthyakorn, Pachara Tinamat
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Abstract

This research aims to investigate customer satisfaction in cosmetic products by utilizing a low-cost tool, word cloud, to analyze online reviews, based on the research questions: how customers feel about each type of cosmetic products? what their feedbacks are? and which words are positive and which ones are negative? The dataset for the investigation comprises with reviews over a 4-year duration of data collection from 2015-2018, collected from popular social networking sites in Thailand including Facebook and Pantip. A hierarchical clustering approach, the Linkage algorithm, was employed in the context of text mining. The result shows that factors that influence customer satisfaction are based on customer experience affecting positive or negative words in online reviews of each product.
泰国化妆品顾客满意度的词云分析
本研究旨在调查消费者对化妆品的满意度,利用一种低成本的工具,词云,分析在线评论,基于研究问题:顾客对每种化妆品的感受?他们的反馈是什么?哪些词是积极的,哪些是消极的?调查的数据集包括2015-2018年4年期间收集的数据,收集自泰国流行的社交网站,包括Facebook和Pantip。在文本挖掘的背景下,采用了一种层次聚类方法,即联动算法。结果表明,影响顾客满意度的因素是基于顾客体验对每个产品在线评论中积极或消极词语的影响。
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