{"title":"Same App, Different App Stores: A Comparative Study","authors":"Mohamed Ali, Mona Erfani Joorabchi, A. Mesbah","doi":"10.1109/MOBILESoft.2017.3","DOIUrl":null,"url":null,"abstract":"To attract more users, implementing the same mobile app for different platforms has become a common industry practice. App stores provide a unique channel for users to share feedback on the acquired apps through ratings and textual reviews. However, each mobile platform has its own online store for distributing apps to users. To understand the characteristics of and discrepancies in how users perceive the same app implemented for and distributed through different platforms, we present a large-scale comparative study of cross-platform apps. We mine the characteristics of 80,000 app-pairs (160K apps in total) from a corpus of 2.4 million apps collected from the Apple and Google Play app stores. We quantitatively compare their app-store attributes, such as stars, versions, and prices. We measure the aggregated user-perceived ratings and find many discrepancies across the platforms. Further, we employ machine learning to classify 1.7 million textual user reviews obtained from 2,000 of the mined app-pairs. We analyze discrepancies and root causes of user complaints to understand cross-platform development challenges that impact cross-platform user-perceived ratings. We also follow up with the developers to understand the reasons behind identified discrepancies.","PeriodicalId":281934,"journal":{"name":"2017 IEEE/ACM 4th International Conference on Mobile Software Engineering and Systems (MOBILESoft)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"56","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/ACM 4th International Conference on Mobile Software Engineering and Systems (MOBILESoft)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MOBILESoft.2017.3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 56
Abstract
To attract more users, implementing the same mobile app for different platforms has become a common industry practice. App stores provide a unique channel for users to share feedback on the acquired apps through ratings and textual reviews. However, each mobile platform has its own online store for distributing apps to users. To understand the characteristics of and discrepancies in how users perceive the same app implemented for and distributed through different platforms, we present a large-scale comparative study of cross-platform apps. We mine the characteristics of 80,000 app-pairs (160K apps in total) from a corpus of 2.4 million apps collected from the Apple and Google Play app stores. We quantitatively compare their app-store attributes, such as stars, versions, and prices. We measure the aggregated user-perceived ratings and find many discrepancies across the platforms. Further, we employ machine learning to classify 1.7 million textual user reviews obtained from 2,000 of the mined app-pairs. We analyze discrepancies and root causes of user complaints to understand cross-platform development challenges that impact cross-platform user-perceived ratings. We also follow up with the developers to understand the reasons behind identified discrepancies.