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http://dx.doi.org/10.5392/JKCA.2022.22.01.058

A Study on Building an Integrated Model of App Performance Analysis and App Review Sentiment Analysis  

Kim, Dongwook (한국과학기술원 기술경영전문대학원)
Kim, Sungbum (금오공대 IT융합학과)
Publication Information
The Journal of the Korea Contents Association / v.22, no.1, 2022 , pp. 58-73 More about this Journal
Abstract
The purpose of this study is to construct a predictable estimation model that reflects the relationship between the variables of mobile app performance and to verify how app reviews affect app performance. In study 1 and 2, the relationship between app performance indicators was derived using correlation analysis and random forest regression estimation of machine learning, and app performance estimation modeling was performed. In study 3, sentiment scores for app reviews were by using sentiment analysis of text mining, and it was found that app review sentiment scores have an effect one lag ahead of the number of daily installations of apps when using multivariate time series analysis. By analyzing the dissatisfaction and needs raised by app performance indicators and reviews of apps, companies can improve their apps in a timely manner and derive the timing and direction of marketing promotions.
Keywords
App Performance Indicator; App Review; Machine Learning; Sentiment Analysis; Multivariate Time Series;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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