TY - GEN
T1 - Sentiment analysis of commit comments in GitHub
T2 - 11th International Working Conference on Mining Software Repositories, MSR 2014
AU - Guzman, Emitza
AU - Azócar, David
AU - Li, Yang
PY - 2014/5/31
Y1 - 2014/5/31
N2 - Emotions have a high impact in productivity, task quality, creativity, group rapport and job satisfaction. In this work we use lexical sentiment analysis to study emotions expressed in commit comments of different open source projects and analyze their relationship with different factors such as used programming language, time and day of the week in which the commit was made, team distribution and project approval. Our results show that projects developed in Java tend to have more negative commit comments, and that projects that have more distributed teams tend to have a higher positive polarity in their emotional content. Additionally, we found that commit comments written on Mondays tend to a more negative emotion. While our results need to be confirmed by a more representative sample they are an initial step into the study of emotions and related factors in open source projects.
AB - Emotions have a high impact in productivity, task quality, creativity, group rapport and job satisfaction. In this work we use lexical sentiment analysis to study emotions expressed in commit comments of different open source projects and analyze their relationship with different factors such as used programming language, time and day of the week in which the commit was made, team distribution and project approval. Our results show that projects developed in Java tend to have more negative commit comments, and that projects that have more distributed teams tend to have a higher positive polarity in their emotional content. Additionally, we found that commit comments written on Mondays tend to a more negative emotion. While our results need to be confirmed by a more representative sample they are an initial step into the study of emotions and related factors in open source projects.
KW - Human factors in software engineering
KW - Sentiment analysis
UR - http://www.scopus.com/inward/record.url?scp=84920701994&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84920701994&partnerID=8YFLogxK
U2 - 10.1145/2597073.2597118
DO - 10.1145/2597073.2597118
M3 - Conference contribution
AN - SCOPUS:84920701994
T3 - 11th Working Conference on Mining Software Repositories, MSR 2014 - Proceedings
SP - 352
EP - 355
BT - 11th Working Conference on Mining Software Repositories, MSR 2014 - Proceedings
PB - Association for Computing Machinery, Inc
Y2 - 31 May 2014 through 1 June 2014
ER -