健康塑身App使用者回饋與更新對評價變化之關係

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2021

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近年健康塑身類App使用人數提升,平台上健康塑身App也呈增加趨勢,過去研究指出使用者回饋與更新分別能提升App評價,但未釐清三者之關係。研究目的為透過內容探勘與統計分析方式探討熱門健康塑身類App中使用者回饋、評價與更新三者之關係,使用關鍵字擷取系統萃取使用者回饋中的評論內容,並分析App更新版本釋出後的使用者回饋與評價之變化。蒐集2020年9月1日Google Play的「健康塑身」類別前100名熱門App之頁面資訊作為研究對象,後續至2021年3月1日總共 6個月為研究時間範圍。研究工具為CATAR內容探勘工具、關鍵字擷取系統、SPSS統計分析軟體與SmartPLS。結果發現健康塑身App內容可分成鍛鍊、監測與日記三類型,使用者正負評中多在意資訊與系統品質方面的問題。整體使用者回饋對於評價有直接影響,更新不具中介效果,研究結果有助開發商能針對使用者回饋、評價與更新三者變化提升產品與服務,並應用於不同類別的App研究。
There is a growing number of health and fitness apps users in recent years, and the number of Health and Fitness Apps on platforms has a trend of increasing as well. Past researchs showed user feedbacks and updates respectively enhance app evaluation, but they haven’t clarified the relationships among the three dimensions. The purpose of this research is to explore the relationships among user feedbacks, evaluation, and updates in popular Health and Fitness apps through content exploration and statistical analysis. This research applyed keyword extraction system to explore the content of comments in user feedbacks, and analyzed the changes in user feedbacks and evaluation after the release of the updated versions. This research gathered the page information of the top 100 popular apps in the category “Health and Fitness” of Google Play on September 1st, 2020 as main research subjects. The research lasted 6 months, until March 1st, 2021. Research tools are CATAR, Keyword Extraction System, SPSS and SmartPLS. The result shows that the content of Health and Fitness App can be categorized into three types, respectively Coaching, Monitoring and Diary. Most positive and negative reviews pointed out the issues of information and system quality. Overall, user feedbacks have direct influence on evaluation, while updates have no intermediary effect. The result provided App developers with methods to evaluate their products and services in response to the changes of user feedbacks, evaluation and updates, and it can be applied to the different category of App research.

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關鍵字擷取, 平台更新, 使用者回饋, Google Play, key-word extraction, platform update, user feedback, Google Play

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