Customer Experience Analysis Skincare Products Through Social Media Data Using Topic Modeling and Sentiment Analysis

Muhammad Habibi, Kartikadyota Kusumaningtyas
{"title":"Customer Experience Analysis Skincare Products Through Social Media Data Using Topic Modeling and Sentiment Analysis","authors":"Muhammad Habibi, Kartikadyota Kusumaningtyas","doi":"10.31328/jsae.v6i1.4169","DOIUrl":null,"url":null,"abstract":"Currently, skin care products (skincare) are popular among the public. Both men and women are interested in buying skin care products. Moreover, there are many brands of skin care products that are divided into several types of facial and body care, such as moisturizers, toners, cleansers, and masks. Therefore, many consumers take the time to find information, for example, in terms of price, quality, and brand for decision-making. A lot of useful information is in the form of Twitter messages known as tweets which are sent from people who use skin care products because Twitter is one of the online social media where users can share their opinions and experiences. However, consumers still have to spend a lot of time searching, reading, and understanding the comprehensive collection of tweets before buying skin care products.The purpose of this study is to analyze customer experience, analyzing automated tweets about skin care products. Tweets about skin care products will be subjected to a topic modeling process to find out what topics are being discussed. In addition, the topics that have been obtained will be subject to sentiment analysis in the form of positive and negative messages for skin care products. Consumers who are app users don’t waste time reading and analyzing large amounts of data manually and they can decide to buy skin care products more easily.The results of this study obtained 14 topics of discussion related to skincare. Meanwhile, the sentiment analysis results of 14 topics resulted in more positive sentiment class tweets overall. It related the category topic that has the number of tweets to the importance of skincare. In addition, categories related to ingredients for skincare products from nature, namely fruits and spices, are the topics that have the second highest number of tweets. The results of the analysis of tweets related to user experience on Twitter, it was found that users prefer skincare products that use ingredients from nature.","PeriodicalId":13778,"journal":{"name":"International Journal of Applied Science and Engineering","volume":"206 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Applied Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31328/jsae.v6i1.4169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Currently, skin care products (skincare) are popular among the public. Both men and women are interested in buying skin care products. Moreover, there are many brands of skin care products that are divided into several types of facial and body care, such as moisturizers, toners, cleansers, and masks. Therefore, many consumers take the time to find information, for example, in terms of price, quality, and brand for decision-making. A lot of useful information is in the form of Twitter messages known as tweets which are sent from people who use skin care products because Twitter is one of the online social media where users can share their opinions and experiences. However, consumers still have to spend a lot of time searching, reading, and understanding the comprehensive collection of tweets before buying skin care products.The purpose of this study is to analyze customer experience, analyzing automated tweets about skin care products. Tweets about skin care products will be subjected to a topic modeling process to find out what topics are being discussed. In addition, the topics that have been obtained will be subject to sentiment analysis in the form of positive and negative messages for skin care products. Consumers who are app users don’t waste time reading and analyzing large amounts of data manually and they can decide to buy skin care products more easily.The results of this study obtained 14 topics of discussion related to skincare. Meanwhile, the sentiment analysis results of 14 topics resulted in more positive sentiment class tweets overall. It related the category topic that has the number of tweets to the importance of skincare. In addition, categories related to ingredients for skincare products from nature, namely fruits and spices, are the topics that have the second highest number of tweets. The results of the analysis of tweets related to user experience on Twitter, it was found that users prefer skincare products that use ingredients from nature.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
使用主题建模和情感分析,通过社交媒体数据分析护肤产品的客户体验
目前,护肤品(护肤)受到大众的欢迎。男性和女性都对购买护肤品感兴趣。此外,有许多品牌的护肤品,分为几种类型的面部和身体护理,如保湿霜,爽肤水,洁面乳和面膜。因此,许多消费者会花时间去查找信息,例如在价格、质量、品牌等方面进行决策。很多有用的信息都是以Twitter消息的形式出现的,这些消息是使用护肤品的人发送的,因为Twitter是用户可以分享他们的观点和经验的在线社交媒体之一。然而,消费者在购买护肤品之前,仍然需要花费大量的时间来搜索、阅读和理解综合的推文。这项研究的目的是分析客户体验,分析关于护肤品的自动推文。有关护肤产品的推文将受到主题建模过程的影响,以找出正在讨论的主题。此外,获得的主题将以护肤品正面和负面信息的形式进行情绪分析。使用app的消费者不会浪费时间手动阅读和分析大量数据,他们可以更容易地决定购买护肤品。本研究结果获得了14个与护肤相关的话题讨论。同时,14个话题的情绪分析结果显示,总体而言,情绪类推文更加积极。它将推特数量的类别主题与护肤的重要性联系起来。此外,与天然护肤品成分相关的类别,即水果和香料,是推特数量第二高的话题。对Twitter上与用户体验相关的推文进行分析的结果发现,用户更喜欢使用天然成分的护肤品。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
International Journal of Applied Science and Engineering
International Journal of Applied Science and Engineering Agricultural and Biological Sciences-Agricultural and Biological Sciences (all)
CiteScore
2.90
自引率
0.00%
发文量
22
期刊介绍: IJASE is a journal which publishes original articles on research and development in the fields of applied science and engineering. Topics of interest include, but are not limited to: - Applied mathematics - Biochemical engineering - Chemical engineering - Civil engineering - Computer engineering and software - Electrical/electronic engineering - Environmental engineering - Industrial engineering and ergonomics - Mechanical engineering.
期刊最新文献
Influence of Annealing on Warping Angle on Polylactic Acid in Fused Deposition Modeling 3D Printer Image Classification of Tempe Fermentation Maturity Using Naïve Bayes Based on Linear Discriminant Analysis Analysis of Hydrogen Gas Production Results in Water Electrolysis Process on Genset Characteristics The Effect of Using a Heat Collection Filter on the Efficiency of Heat Absorption from the Flame of LPG Gas Fuel Redesign of Facilities Layout Using Computerized Relationship Planning (CORELAP) and Computerized Relative Allocation of Facilities Techniques (CRAFT) Methods
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1