Analysis of user comments: An approach for software requirements evolution
By Laura V. Galvis Carreño, Kristina Winbladh. International Conference on Software Engineering, 2013
339 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems
View Paper: https://www.semanticscholar.org/paper/319f029db50f8805bfc6836ade88198d4ff6f402
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Mark Harman
- Yue Jia
- Yuanyuan Zhang
- William J. Martin
- Federica Sarro
- Emitzá Guzmán
- Walid Maalej
- Gerardo Canfora
In Information Systems
- Yue Jia
- Mark Harman
- Yuanyuan Zhang
- Walid Maalej
- Hadeer Nabil
- Emitzá Guzmán
- Federica Sarro
- William J. Martin
Citations in the corpus
- Bug report, feature request, or simply praise? On automatically classifying app reviews (2015, background): “A significant amount of the reviews include requirements-related information such as bugs or issues [27], summary of the user experience with certain features [12], requests for enhancements [18], and even ideas for new features [8], [27].”
- A Survey of App Store Analysis for Software Engineering (2017, methodology): “Galvis Carre~ no and Winbladh [69] extracted user requirements from comments using the ASUM model [111], a sentiment-aware topic model.”
- AR-miner: mining informative reviews for developers from mobile app marketplace (2014, methodology): “First, we qualitatively compare our scheme (which contains a filtering step before grouping) with the baseline scheme used in [22] (which directly applies topic models).”
- How can i improve my app? Classifying user reviews for software maintenance and evolution (2015, background): “App developers spend considerable effort in collecting and exploiting user feedback to improve user satisfaction.”