earticle

영어

This study aimed to analyze a network of beauty creators using big data, employing Textom and UCINET for the analysis. To achieve this, data were collected over one year from NAVER, DAUM, Google, and YouTube. The findings revealed the following: First, in terms of beauty creator-related keywords, creator was most frequently mentioned, followed by beauty, content, product, beauty creator, brand, makeup, skin, YouTube, fashion, recommendation, video, activity, influencer, NAVER, cosmetics, South Korea, marketing, consumer review and short form. Second, the network structure was visualized using NetDraw, which illustrated the relationships among the keywords. Third, using CONCOR for big data analysis, four distinct groups were identified: Content Production, Introduction of Cosmetics, Content Subscription, and Makeup Artist.

중국어

本研究旨在于探索基于大数据的美容创作者关系网络，分析方法采用了Textom和UCINET，资料收集渠道限定为Naver、Daum、谷歌、YouTube，为期1年。研究结果为如下：第一、美容创作者相关关键词频率分析调查显示，从高到低依次为美容创作者、美容、化妆内容、产品、美容创作者、品牌、化妆、皮肤、YouTube、时尚、推荐、视频、活动、网红、Naver、化妆品、韩国、市场营销、评价、短视频。第二、本研究利用NetDraw能够可视化整个关系网络结构，掌握各关键词之间的相互关系。第三、基于CONCOR的大数据分析结果显示，可以将关键划分为4个组合，分别是内容制作、化妆品介绍、内容订阅、化妆师。