App Store Analysis: Mining App Stores for Relationships between Customer, Business and Technical Characteristics

作者: A Finkelstein , F Sarro , M Harman , Y Jia , Y Zhang

DOI:

关键词: Information retrievalRank (computer programming)PopularityRecallApp storeComputer science

摘要: This paper argues that App Store Analysis can be used to understand the rich interplay between app customers and their developers. We use data mining extract price popularity information natural language processing elicit each app�s claimed features from Blackberry Store, revealing strong correlations customer rating (rank of downloads). found evidence for a mild correlation number an also higher priced tended lower rated by users. free apps have significantly (p-value <0.001) than non-free apps, with moderately high effect size (�12 = 0.68). provide initial extracted are meaningful developers (precision 0.71, recall 0.77). All our experiments analysis made available on-line support further analysis.

参考文章(29)
Meiyappan Nagappan, Ahmed E. Hassan, Emad Shihab, Challenges in mobile apps: a multi-disciplinary perspective conference of the centre for advanced studies on collaborative research. pp. 378- 381 ,(2013)
Ben Eaton, Youngjin Yoo, Silvia Elaluf-Calderwood, Carsten Sorensen, Dynamic structures of control and generativity in digital ecosystem service innovation: the cases of the Apple and Google mobile app stores London School of Economics and Political Science. ,(2011)
Tao Xie, Rahul Pandita, William Enck, Xusheng Xiao, Wei Yang, WHYPER: towards automating risk assessment of mobile applications usenix security symposium. pp. 527- 542 ,(2013)
Mark D. Syer, Meiyappan Nagappan, Ahmed E. Hassan, Bram Adams, Revisiting prior empirical findings for mobile apps: an empirical case study on the 15 most popular open-source Android apps conference of the centre for advanced studies on collaborative research. pp. 283- 297 ,(2013)
Mark Harman, Yue Jia, Yuanyuan Zhang, App store mining and analysis: MSR for app stores mining software repositories. pp. 108- 111 ,(2012) , 10.5555/2664446.2664461
M.M. Lehman, On understanding laws, evolution, and conservation in the large-program life cycle Journal of Systems and Software. ,vol. 1, pp. 213- 221 ,(1979) , 10.1016/0164-1212(79)90022-0
R. Minelli, M. Lanza, Software Analytics for Mobile Applications--Insights a Lessons Learned conference on software maintenance and reengineering. pp. 144- 153 ,(2013) , 10.1109/CSMR.2013.24
Tim Menzies, Beyond data mining; towards "idea engineering" predictive models in software engineering. pp. 11- ,(2013) , 10.1145/2499393.2499401
Soo Ling Lim, Peter J. Bentley, Investigating app store ranking algorithms using a simulation of mobile app ecosystems congress on evolutionary computation. pp. 2672- 2679 ,(2013) , 10.1109/CEC.2013.6557892
Mario Linares-Vásquez, Andrew Holtzhauer, Carlos Bernal-Cárdenas, Denys Poshyvanyk, Revisiting Android reuse studies in the context of code obfuscation and library usages Proceedings of the 11th Working Conference on Mining Software Repositories - MSR 2014. pp. 242- 251 ,(2014) , 10.1145/2597073.2597109