Sentiment analysis of commit comments in GitHub: An empirical study

Emitza Guzman, David Azócar, Yang Li

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

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.

Original languageEnglish
Title of host publication11th Working Conference on Mining Software Repositories, MSR 2014 - Proceedings
PublisherAssociation for Computing Machinery, Inc
Pages352-355
Number of pages4
ISBN (Electronic)9781450328630
DOIs
Publication statusPublished - 31 May 2014
Externally publishedYes
Event11th International Working Conference on Mining Software Repositories, MSR 2014 - Hyderabad, India
Duration: 31 May 20141 Jun 2014

Publication series

Name11th Working Conference on Mining Software Repositories, MSR 2014 - Proceedings

Conference

Conference11th International Working Conference on Mining Software Repositories, MSR 2014
CountryIndia
CityHyderabad
Period31/05/141/06/14

Keywords

  • Human factors in software engineering
  • Sentiment analysis

Fingerprint

Dive into the research topics of 'Sentiment analysis of commit comments in GitHub: An empirical study'. Together they form a unique fingerprint.

Cite this