Developer Behavior and Sentiment from Data Mining Open Source Repositories

被引:7
作者
Robinson, William N. [1 ]
Deng, Tianjie [2 ]
Qi, Zirun [1 ]
机构
[1] Georgia State Univ, Comp Informat Syst Dept, Atlanta, GA 30303 USA
[2] Univ Denver, Dept Business Informat & Analyt, Denver, CO USA
来源
PROCEEDINGS OF THE 49TH ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES (HICSS 2016) | 2016年
关键词
OPEN SOURCE SOFTWARE; OPEN SOURCE PROJECTS; ORGANIZATIONAL ROUTINES; PARTICIPATION; PERFORMANCE; COMPLEXITY;
D O I
10.1109/HICSS.2016.465
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Developer sentiment may wax and wane as a project progresses. Open-source projects that attract and retain developers tend to be successful. It may be possible to predict project success, in part, if one can measure developer behavior and sentiment-projects with active, happy developers are more likely to succeed. We have analyzed GitHub. com projects in an attempt to model these concepts. We have data mined 124 projects from GitHub.com . The projects were automatically mined using sequence mining methods to derive a behavioral model of developer activities. The projects were also mined for developer sentiment. Finally, a regression model shows how sentiment varies with behavioral differences -a change in behavior is correlated with a change in sentiment. The relationship between sentiment and success is not directly explored, herein. This research project is a preliminary step in a larger research project aimed at understanding and monitoring FLOSS projects using a process modeling approach.
引用
收藏
页码:3729 / 3738
页数:10
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