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App Update Patterns: How Developers Act on User Reviews in Mobile App Stores

  • Shance Wang
  • Zhongjie WangEmail author
  • Xiaofei Xu
  • Quan Z. Sheng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10601)

Abstract

Mobile app stores receive numerous reviews that contain valuable feedbacks raised by users. Incorporating user reviews into iterative delivery of new App versions would improve the quality and ratings of Apps. To date, there is no explicit answer on whether and to what degree App developers make use of user reviews sufficiently and timely. In this paper, we extract requested features in user reviews and updated features in new versions, identify the latent relation between them, and discover 7 types of Update Patterns (UPs) by grouping similar Atomic Update Units (AUs). UPs delineate common behavioral characteristics of acting on user reviews from perspectives of feature intensity trend, sufficiency and responsiveness. Statistics are conducted to explore the similarity/difference between exhibited update patterns w.r.t. Apps, features, and time. Results would help developers get a clear understanding on their own habits on how to act on user reviews, and thus offer suggestions on utilizing user reviews more efficiently in App development.

Keywords

Mobile App App store User review Atomic Update Unit (AU) Update Pattern (UP) Empirical study 

Notes

Acknowledgments

Work in this paper is supported by the Natural Science Foundation of China (No. 61772155, 61472106).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Shance Wang
    • 1
  • Zhongjie Wang
    • 1
    Email author
  • Xiaofei Xu
    • 1
  • Quan Z. Sheng
    • 2
  1. 1.Harbin Institute of TechnologyHarbinChina
  2. 2.Macquarie UniversitySydneyAustralia

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