Designing the Next Mobile App Recommender System for the Globe

Innovative mobile applications bring radical changes to people's life around the globe. With its unique characteristics of anywhere, anytime accessibility, thousands of mobile apps are developed, distributed, and executed over the Internet. To understand the selection criteria for different end users when facing a mobile application, this paper quests for an evaluation framework for mobile apps based statistical data analysis and survey. Firstly, user's ratings on 1500+ mobile applications from Google Play were analyzed to elicit different users' preferences on mobile apps. The data was extracted twice, first at the end 2015, then early 2017, and the data are from four different locations: The UK, USA, Netherland, and Pakistan. Secondly, the survey was conducted to collect university students' rationale when making selections and downloading decisions of a mobile app. Furthermore, the knowledge gathered from data and survey is used to propose a systematic evaluation framework. Finally, the proposed framework is used to develop a recommender system for the mobile app markets. The implementation of the recommender system is introduced, and which was further verified by an example case.

[1]  Xiaodong Wang,et al.  Measuring the Mobile App Market: A Complex Network Approach , 2013 .

[2]  Hongji Yang,et al.  The creative turn: new challenges for computing , 2013, Int. J. Creative Comput..

[3]  Peter J. Bentley,et al.  Investigating Country Differences in Mobile App User Behavior and Challenges for Software Engineering , 2015, IEEE Transactions on Software Engineering.

[4]  A. Andrews,et al.  4 Requirements Prioritization , .

[5]  Florian Michahelles,et al.  Google play is not a long tail market: an empirical analysis of app adoption on the Google play app market , 2013, SAC '13.

[6]  Ahmed E. Hassan,et al.  Fresh apps: an empirical study of frequently-updated mobile apps in the Google play store , 2015, Empirical Software Engineering.

[7]  Timo Knuutila,et al.  App Store, Marketplace, Play! An Analysis of Multi-Homing in Mobile Software Ecosystems , 2012, IWSECO@ICSOB.

[8]  Yuanyuan Zhang,et al.  App store mining and analysis: MSR for app stores , 2012, 2012 9th IEEE Working Conference on Mining Software Repositories (MSR).

[9]  Fernando Leandro dos Santos,et al.  The Role of Text Pre-processing in Opinion Mining on a Social Media Language Dataset , 2014, 2014 Brazilian Conference on Intelligent Systems.

[10]  Hiep Phuc Luong,et al.  Conceptual recommender system for CiteSeerX , 2009, RecSys '09.

[11]  J. Bobadilla,et al.  Recommender systems survey , 2013, Knowl. Based Syst..

[12]  Kon Mouzakis,et al.  A preliminary analysis of vocabulary in mobile app user reviews , 2012, OZCHI.

[13]  Lars Schmidt-Thieme,et al.  Proceedings of the third ACM conference on Recommender systems , 2008, RecSys 2008.

[14]  Emily R Breton,et al.  Weight loss—there is an app for that! But does it adhere to evidence-informed practices? , 2011, Translational behavioral medicine.

[15]  Nicole Fassbinder.  Cultures And Organizations Software Of The Mind Intercultural Cooperation And Its Importance For Survival , 2016 .

[16]  Otto Petrovic,et al.  Learning Mobile App Design from User Review Analysis , 2011, Int. J. Interact. Mob. Technol..

[17]  Ivano Malavolta,et al.  End Users' Perception of Hybrid Mobile Apps in the Google Play Store , 2015, 2015 IEEE International Conference on Mobile Services.

[18]  Oliver Günther,et al.  Privacy in e-commerce: stated preferences vs. actual behavior , 2005, CACM.

[19]  Adrian Holzer,et al.  Mobile application market: A developer's perspective , 2011, Telematics Informatics.

[20]  David A. Wagner,et al.  Do Android users write about electric sheep? Examining consumer reviews in Google Play , 2013, 2013 IEEE 10th Consumer Communications and Networking Conference (CCNC).

[21]  Gayatri Venugopal,et al.  A Review of Popular Applications on Google Play - Do They Cater to Visually Impaired Users? , 2015, ArXiv.

[22]  Daniel Gatica-Perez,et al.  Mining large-scale smartphone data for personality studies , 2013, Personal and Ubiquitous Computing.

[23]  Lin Liu.  When intelligence meets data: game story generation by compositional creativity , 2016, Int. J. Creative Comput..

[24]  Fatna Belqasmi,et al.  Identification and analysis of free games' permissions in Google Play , 2015, 2015 6th International Conference on Information and Communication Systems (ICICS).

[25]  G. Hofstede.  Culture and Organizations , 1980 .

[26]  Hoon Seok Choi,et al.  Effects of Freemium Strategy in the Mobile App Market: An Empirical Study of Google Play , 2014, J. Manag. Inf. Syst..

[27]  Christos Faloutsos,et al.  Why people hate your app: making sense of user feedback in a mobile app store , 2013, KDD.

[28]  Mihhail Matskin,et al.  Mining and Analysis of Apps in Google Play , 2013, WEBIST.

[29]  Jason Nieh,et al.  A measurement study of google play , 2014, SIGMETRICS '14.

[30]  Orrin I. Franko,et al.  Smartphone App Use Among Medical Providers in ACGME Training Programs , 2012, Journal of Medical Systems.

[31]  Volker Wulf,et al.  Data collection in global software engineering research: learning from past experience , 2012, Empirical Software Engineering.

[32]  Kon Mouzakis,et al.  A preliminary analysis of mobile app user reviews , 2012, OZCHI.

[33]  Teresa de la Hera Conde-Pumpido,et al.  A Conceptual Model for the Study of Persuasive Games , 2013, DiGRA Conference.

[34]  Mir Riyanul Islam.  Numeric rating of Apps on Google Play Store by sentiment analysis on user reviews , 2014, 2014 International Conference on Electrical Engineering and Information & Communication Technology.

[35]  Anthony I. Wasserman,et al.  Software engineering issues for mobile application development , 2010, FoSER '10.

[36]  Paul Resnick,et al.  Recommender systems , 1997, CACM.

[37]  James D. Herbsleb,et al.  Global Software Engineering: The Future of Socio-technical Coordination , 2007, Future of Software Engineering (FOSE '07).

[38]  Yang Li,et al.  Teaching Global Software Engineering: Interactive Exercises for the Classroom , 2014, 2014 IEEE 9th International Conference on Global Software Engineering.