A study of changes in user experience and service evaluation: Topic modeling of Netflix app reviews

Seon Yeong Yu, Mijin Noh, Yangsok Kim, Mumoungcho Han
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Abstract

As Netflix usage has increased due to the COVID-19 pandemic, users' experiences with the service have also increased. Therefore, this study aims to conduct topic modeling analysis based on Netflix review data to explore the changes in Netflix user experience and service before and after the COVID-19 pandemic. We collected Netflix app review data from the Google Play Store using the Google Play Scraper library, and used topic modeling to examine keyword differences between app reviews before and after the pandemic. The analysis revealed four main topics: Netflix app features, Netflix content, Netflix service usage, and Netflix overall reviews. After the pandemic, when user experience increased, users tended to use more diverse and detailed keywords in their reviews. By using Netflix review data to analyze users' opinions, this study shows the changes in user experience of Netflix services before and after the pandemic, which can be used as a guide to strengthen competitiveness in the competitive OTT market.
用户体验与服务评价的变化研究:Netflix应用评论的主题建模
受新型冠状病毒感染症(COVID-19)的影响,Netflix的使用率增加,用户的体验也随之增加。因此,本研究旨在基于Netflix评论数据进行主题建模分析,探讨COVID-19大流行前后Netflix用户体验和服务的变化。我们使用Google Play Scraper库从Google Play Store收集Netflix应用评论数据,并使用主题建模来检查疫情前后应用评论之间的关键字差异。该分析揭示了四个主要主题:Netflix应用程序功能、Netflix内容、Netflix服务使用情况和Netflix总体评价。疫情后,用户体验增加,用户在评论中使用的关键词更多样化、更详细。本研究通过使用Netflix的评论数据分析用户的意见,展示了疫情前后Netflix服务的用户体验变化,可以作为在竞争激烈的OTT市场中增强竞争力的指导。
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