Publication | Closed Access
App store mining and analysis: MSR for app stores
248
Citations
8
References
2012
Year
Unknown Venue
Software MaintenanceEngineeringApplication ProfileBusiness IntelligenceCustomer ProfilingSoftware EngineeringApp Store MsrBusiness AnalyticsSoftware AnalysisText MiningMobile AnalyticsMobile MarketingInformation RetrievalData ScienceData MiningManagementSoftware Repository MiningSoftware MiningKnowledge DiscoveryApplication AnalysisMarketingApp Store Mining
This paper introduces app store mining and analysis as a form of software repository mining. Unlike other software repositories traditionally used in MSR work, app stores usually do not provide source code. However, they do provide a wealth of other information in the form of pricing and customer reviews. Therefore, we use data mining to extract feature information, which we then combine with more readily available information to analyse apps' technical, customer and business aspects. We applied our approach to the 32,108 non-zero priced apps available in the Blackberry app store in September 2011. Our results show that there is a strong correlation between customer rating and the rank of app downloads, though perhaps surprisingly, there is no correlation between price and downloads, nor between price and rating. More importantly, we show that these correlation findings carry over to (and are even occasionally enhanced within) the space of data mined app features, providing evidence that our `App store MSR' approach can be valuable to app developers.
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