The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
User feedback in the appstore: An empirical study
Abstract
Application distribution platforms - or app stores - such as Google Play or Apple AppStore allow users to submit feedback in form of ratings and reviews to downloaded applications. In the last few years, these platforms have become very popular to both application developers and users. However, their real potential for and impact on requirements engineering processes are not yet well understood. This paper reports on an exploratory study, which analyzes over one million reviews from the Apple AppStore. We investigated how and when users provide feedback, inspected the feedback content, and analyzed its impact on the user community. We found that most of the feedback is provided shortly after new releases, with a quickly decreasing frequency over time. Reviews typically contain multiple topics, such as user experience, bug reports, and feature requests. The quality and constructiveness vary widely, from helpful advices and innovative ideas to insulting offenses. Feedback content has an impact on download numbers: positive messages usually lead to better ratings and vice versa. Negative feedback such as shortcomings is typically destructive and misses context details and user experience. We discuss our findings and their impact on software and requirements engineering teams.
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Cites
Mining association rules between sets of items in large databases
Agrawal, R., Imieliński, T., & Swami, A. (1993) · Proceedings of the 1993 ACM SIGMOD international conference on Management of data · doi:10.1145/170035.170072 · Cited by 14,907
The Content Analysis Guidebook
Neuendorf, K. A. (2017) · doi:10.4135/9781071802878 · Cited by 9,286 · cited 1×
“To explore the feedback content and find included topics, two researchers independently performed a manual content analysis [11] of a random sample from our data set.”
MethodSelecting Empirical Methods for Software Engineering Research
Easterbrook, S., Singer, J., Storey, M.-A., & Damian, D. (2008) · Guide to Advanced Empirical Software Engineering · doi:10.1007/978-1-84800-044-5_11 · Cited by 1,167
Cited by
AR-miner: mining informative reviews for developers from mobile app marketplace
Chen, N., Lin, J., Hoi, S. C. H., Xiao, X., & Zhang, B. (2014) · Proceedings of the 36th International Conference on Software Engineering · doi:10.1145/2568225.2568263 · Cited by 517
A Survey of App Store Analysis for Software Engineering
Martin, W., Sarro, F., Jia, Y., Zhang, Y., & Harman, M. (2017) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2016.2630689 · Cited by 459
How can i improve my app? Classifying user reviews for software maintenance and evolution
Panichella, S., Di Sorbo, A., Guzman, E., Visaggio, C. A., Canfora, G., & Gall, H. C. (2015) · 2015 IEEE International Conference on Software Maintenance and Evolution (ICSME) · doi:10.1109/icsm.2015.7332474 · Cited by 455
What would users change in my app? summarizing app reviews for recommending software changes
Di Sorbo, A., Panichella, S., Alexandru, C. V., Shimagaki, J., Visaggio, C. A., Canfora, G., & Gall, H. C. (2016) · Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering · doi:10.1145/2950290.2950299 · Cited by 294
Dehling, T., Gao, F., Schneider, S., & Sunyaev, A. (2015) · JMIR mHealth and uHealth · doi:10.2196/mhealth.3672 · Cited by 243
Metadata
- Authors
- Pagano, D., & Maalej, W.
- Venue
- 2013 21st IEEE International Requirements Engineering Conference (RE)
- Publisher
- IEEE
- Published
- 2013-07
- Pages
- 125-134
- OpenAlex
- W2085465189
- Cited by
- 540
- References
- 3
- FWCI
- 25.56
- Type
- conference paper
- Language
- en
- Open access
- closed
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