How Do Users Like This Feature? A Fine Grained Sentiment Analysis of App Reviews
By Emitzá Guzmán, Walid Maalej. IEEE International Requirements Engineering Conference, 2014
650 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems
View Paper: https://www.semanticscholar.org/paper/030ea3f854d688659500a949eac095cdba087682
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
- Ke Mao
- Walid Maalej
In Information Systems
Citations in the corpus
- How can i improve my app? Classifying user reviews for software maintenance and evolution (2015, background): “We thank Francesco Mercaldo (Ph.D. Student at the University of Sannio) for his help in the results’ manual validation.”
- A Survey of App Store Analysis for Software Engineering (2017, methodology): “[36], 2014 g PIR 6,938 Guzman and Maalej [88], 2014 a,g RE 7 Khalid et al.”
- A survey of the use of crowdsourcing in software engineering (2017, background): “The growth in the use of app stores as a platform for software deployment and review (Harman et al., 2012; Pagano and Maalej, 2013; Guzman and Maalej, 2014; Chen et al., 2014), is already providing a kind of Hybrid Crowdsourced 1835 Software Engineering.”
- 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].”