How Do Users Like This Feature? A Fine Grained Sentiment Analysis of App Reviews
Technical University of Munich · Universität Hamburg
Abstract
App stores allow users to submit feedback for downloaded apps in form of star ratings and text reviews. Recent studies analyzed this feedback and found that it includes information useful for app developers, such as user requirements, ideas for improvements, user sentiments about specific features, and descriptions of experiences with these features. However, for many apps, the amount of reviews is too large to be processed manually and their quality varies largely. The star ratings are given to the whole app and developers do not have a mean to analyze the feedback for the single features. In this paper we propose an automated approach that helps developers filter, aggregate, and analyze user reviews. We use…
Citation impact
- FWCI
- 50.77
- Percentile
- 100%
- References
- 36
Authors
2Topics & keywords
- Computer science
- Filter (signal processing)
- Sentiment analysis
- Aggregate (composite)
- Feature (linguistics)
- Information retrieval
- Recall
- World Wide Web
- Quality Education