@inproceedings{ba40abf77ab04448b430c6e34d461772,
title = "Data analysis of correlation between project popularity and code change frequency",
abstract = "Github is a source code management platform with social networking features that help increase the popularity of a project. The features of the GitHub like watch, star, fork and pull requests help make a project popular among the developers, in addition to enabling them to work on the code together. In this work, we study the relation between the project popularity and the continual code changes made to a GitHub project. The correlation is found by using the metrics such as the number of watchers, pull requests, and the number of commits. We correlate the time series of code change frequency with the time series of project popularity. As a result, we have found that projects with at least 1500 watchers each month have a strong positive correlation between the project popularity and frequency of code changes. We have also found that the number of pull requests is 73.2% more important to the popularity of a project than the number of watchers.",
keywords = "Data analytics, Mining software repositories, Open-source development",
author = "Dabeeruddin Syed and Jadran Sessa and Andreas Henschel and Davor Svetinovic",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 23rd International Conference on Neural Information Processing, ICONIP 2016 ; Conference date: 16-10-2016 Through 21-10-2016",
year = "2016",
doi = "10.1007/978-3-319-46681-1_5",
language = "British English",
isbn = "9783319466804",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "36--43",
editor = "Kazushi Ikeda and Minho Lee and Akira Hirose and Seiichi Ozawa and Kenji Doya and Derong Liu",
booktitle = "Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings",
address = "Germany",
}