User feedback in the appstore: An empirical study
By Dennis Pagano, Walid Maalej. IEEE International Requirements Engineering Conference, 2013
566 citations recorded by the source corpus.
Subfields: Computer Science Applications, Information Systems
View Paper: https://www.semanticscholar.org/paper/2a70f0d172e62d22928c40343bfba0ecbc77e05b
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In Computer Science Applications
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Citations in the corpus
- How can i improve my app? Classifying user reviews for software maintenance and evolution (2015, methodology): “App developers spend considerable effort in collecting and exploiting user feedback to improve user satisfaction.”
- AR-miner: mining informative reviews for developers from mobile app marketplace (2014, background): “In [36], Pagano and Maalej conducted an exploratory study to analyze the user reviews crawled from Apple App Store.”
- 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.”
- A Survey of App Store Analysis for Software Engineering (2017, background): “[42], 2013 a,g WWW 5,059 Pagano and Maalej [175], 2013 a RE 1,100 Hoon et al.”
- How Do Users Like This Feature? A Fine Grained Sentiment Analysis of App Reviews (2014, background): “These numbers confirm previous studies, which have highlighted the large amount of effort needed to manually analyze user feedback [4], [21].”
- Bug report, feature request, or simply praise? On automatically classifying app reviews (2015, methodology): “User experiences combine " helpfulness " and " feature information " content reported by Pagano and Maalej [27].”