DevRank: Mining Influential Developers In Github
Abstract
As the social coding is becoming increasingly popular, understanding the influence of developers can benefit various applications, such as advertisement for new projects and innovations. However, most existing works have focused only on ranking influential nodes in non-weighted and homogeneous networks, which are not able to transfer proper importance scores to the real important node. To rank developers in Github, we define developer's influence on the capacity of attracting attention which can be measured by the number of followers obtained in the future. We further defined a new method, DevRank, which ranks the developers by influence propagation through heterogeneous network constructed according to user behaviors, including "commit" and "follow". Our experiment compares the performance between DevRank and some other link analysis algorithms, the results have shown that DevRank can improve the ranking accuracy.
Cite
@article{arxiv.1710.10427,
title = {DevRank: Mining Influential Developers In Github},
author = {Zhifang Liao and Haozhi Jin and Yifan Li and Benhong Zhao and Jinsong Wu and Shengzong Liu},
journal= {arXiv preprint arXiv:1710.10427},
year = {2017}
}