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Feature-based evaluation of competing apps

Published:14 November 2016Publication History

ABSTRACT

App marketplaces, i.e. Google Play Store and Apple AppStore,comprise many competing apps offering a fair set of similar features. Users of competing apps can submit feedback in the form of ratings and textual comments. The feedback is useful for app developers to get a better understanding of where their app stands in the competition. However, app ratings don’t provide concrete information regarding users’ perceptions about an app’s features compared to similar apps. Studies have shown that users express sentiments on app features in app reviews. Therefore, user reviews are a valuable information source to compare competing apps based on users' sentiments regarding features. So far, researchers have analyzed app reviews to summarize the users’ sentiments on app features but the existing approaches have not been used for the comparison of competing apps. In this direction, we analyze app reviews of 25 apps to extract app features, determine competing apps based on feature commonality, and then compare competing apps based on users’ sentiments regarding features. We developed a tool prototype that helps app developers in identifying features which have been perceived negatively by its users. The tool prototype is also useful to find a set of features loved by users in other similar apps but missing in one’s app. We demonstrate the usefulness of the tool prototype and give pointers to future work.

References

  1. Al-Subaihin, A. et al. 2016. Clustering Mobile Apps Based on Mined Textual Features. 10th International Conference on Empirical Software Engineering and Measurement (2016). Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Chen, N. et al. 2014. AR-miner: mining informative reviews for developers from mobile app marketplace. Proceedings of the 36th International Conference on Software Engineering - ICSE 2014 (New York, New York, USA, 2014), 767–778. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Finkelstein, A. et al. 2014. App Store Analysis : Mining App Stores for Relationships between Customer, Business and Technical Characteristics. UCL Research Note. 14/10, (2014), 1–24.Google ScholarGoogle Scholar
  4. Garcia, D. et al. 2013. The Role of Emotions in Contributors Activity: A Case Study on the GENTOO Community. 2013 International Conference on Cloud and Green Computing (Sep. 2013), 410–417. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Gu, X. and Kim, S. 2015. What parts of your apps are loved by users? Proceedings - 2015 30th IEEE/ACM International Conference on Automated Software Engineering, ASE 2015 (Nov. 2015), 760–770.Google ScholarGoogle Scholar
  6. Guzman, E. and Maalej, W. 2014. How Do Users Like This Feature? A Fine Grained Sentiment Analysis of App Reviews. 2014 IEEE 22nd International Requirements Engineering Conference (RE) (Aug. 2014), 153–162.Google ScholarGoogle ScholarCross RefCross Ref
  7. Jongeling, R. et al. 2015. Choosing your weapons: On sentiment analysis tools for software engineering research. 2015 IEEE International Conference on Software Maintenance and Evolution (ICSME) (Sep. 2015), 531–535. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Keertipati, S. et al. 2016. Approaches for prioritizing feature improvements extracted from app reviews. EASE ’16 Proceedings of the 20th International Conference on Evaluation and Assessment in Software Engineering. (2016). Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Ortu, M. et al. 2015. Are Bullies More Productive? Empirical Study of Affectiveness vs. Issue Fixing Time. 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories (May 2015), 303–313. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Pletea, D. et al. 2014. Security and emotion: sentiment analysis of security discussions on GitHub. Proceedings of the 11th Working Conference on Mining Software Repositories - MSR 2014 (New York, New York, USA, 2014), 348–351. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Thelwall, M. et al. 2010. Sentiment strength detection in short informal text. Journal of the American Society for Information Science and Technology. 61, 12 (Dec. 2010), 2544–2558. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Villarroel, L. et al. 2016. Release planning of mobile apps based on user reviews. Proceedings of the 38th International Conference on Software Engineering - ICSE ’16 (New York, New York, USA, 2016), 14–24. Google ScholarGoogle ScholarDigital LibraryDigital Library

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    • Published in

      cover image ACM Conferences
      WAMA 2016: Proceedings of the International Workshop on App Market Analytics
      November 2016
      56 pages
      ISBN:9781450343985
      DOI:10.1145/2993259

      Copyright © 2016 ACM

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      Publication History

      • Published: 14 November 2016

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