@inproceedings{7c8d5bb4be9a4e9694e17db9751bcd63,
title = "Ensemble methods for app review classification: An approach for software evolution",
abstract = "App marketplaces are distribution platforms for mobile applications that serve as a communication channel between users and developers. These platforms allow users to write reviews about downloaded apps. Recent studies found that such reviews include information that is useful for software evolution. However, the manual analysis of a large amount of user reviews is a tedious and time consuming task. In this work we propose a taxonomy for classifying app reviews into categories relevant for software evolution. Additionally, we describe an experiment that investigates the performance of individual machine learning algorithms and its ensembles for automatically classifying the app reviews. We evaluated the performance of the machine learning techniques on 4550 reviews that were systematically labeled using content analysis methods. Overall, the ensembles had a better performance than the individual classifiers, with an average precision of 0.74 and 0.59 recall.",
keywords = "App Reviews, Software Evolution, Text Classification, User Feedback",
author = "Emitza Guzman and Muhammad El-Haliby and Bernd Bruegge",
year = "2016",
month = jan,
day = "4",
doi = "10.1109/ASE.2015.88",
language = "English",
series = "Proceedings - 2015 30th IEEE/ACM International Conference on Automated Software Engineering, ASE 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "771--776",
booktitle = "Proceedings - 2015 30th IEEE/ACM International Conference on Automated Software Engineering, ASE 2015",
address = "United States",
note = "30th IEEE/ACM International Conference on Automated Software Engineering, ASE 2015 ; Conference date: 09-11-2015 Through 13-11-2015",
}