TY - GEN
T1 - Retrieving Diverse Opinions from App Reviews
AU - Guzman, Emitza
AU - Aly, Omar
AU - Bruegge, Bernd
PY - 2015/11/5
Y1 - 2015/11/5
N2 - Context: Users can have conflicting opinions and different experiences when using software and user reviews serve as a channel in which users can document their opinions and experiences. To develop and evolve software that is usable and relevant for a diverse group of users, different opinions and experiences need to be taken into account. Goal: In this paper we present DIVERSE, a feature and sentiment centric retrieval approach which automatically provides developers with a diverse sample of user reviews that is representative of the different opinions and experiences mentioned in the whole set of reviews. Results: We evaluated the diversity retrieval performance of our approach on reviews from seven apps from two different app stores. We compared the reviews retrieved by DIVERSE with a feature-based retrieval approach and found that on average DIVERSE outperforms the baseline approach. Additionally, a controlled experiment revealed that DIVERSE can help develop- ers save time when analyzing user reviews and was considered useful for detecting conflicting opinions and software evolution. Conclusions: DIVERSE can therefore help developers collect a comprehensive set of reviews and aid in the detection of conflicting opinions.
AB - Context: Users can have conflicting opinions and different experiences when using software and user reviews serve as a channel in which users can document their opinions and experiences. To develop and evolve software that is usable and relevant for a diverse group of users, different opinions and experiences need to be taken into account. Goal: In this paper we present DIVERSE, a feature and sentiment centric retrieval approach which automatically provides developers with a diverse sample of user reviews that is representative of the different opinions and experiences mentioned in the whole set of reviews. Results: We evaluated the diversity retrieval performance of our approach on reviews from seven apps from two different app stores. We compared the reviews retrieved by DIVERSE with a feature-based retrieval approach and found that on average DIVERSE outperforms the baseline approach. Additionally, a controlled experiment revealed that DIVERSE can help develop- ers save time when analyzing user reviews and was considered useful for detecting conflicting opinions and software evolution. Conclusions: DIVERSE can therefore help developers collect a comprehensive set of reviews and aid in the detection of conflicting opinions.
KW - Diversity in Software Engineering
KW - Diversity Opinion Retrieval
KW - Human Factors in Software Engineering
KW - Software Evolution
KW - User Feedback
UR - http://www.scopus.com/inward/record.url?scp=84961595296&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84961595296&partnerID=8YFLogxK
U2 - 10.1109/ESEM.2015.7321214
DO - 10.1109/ESEM.2015.7321214
M3 - Conference contribution
AN - SCOPUS:84961595296
T3 - International Symposium on Empirical Software Engineering and Measurement
SP - 21
EP - 30
BT - 2015 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2015 - Proceedings
PB - IEEE Computer Society
T2 - ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2015
Y2 - 22 October 2015 through 23 October 2015
ER -