TY - GEN
T1 - Analyzing the social ties and structure of contributors in Open Source Software community
AU - Allaho, Mohammad Y.
AU - Lee, Wang Chien
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - We conduct a statistical analysis on the social networks of contributors in Open Source Software (OSS) communities using datasets collected from two most fast-growing OSS social interaction sites, Github.com and Ohloh.net. Our goal is to analyze the connectivity structure of the social networks of contributors and to investigate the effect of the different social tie structures on developers' overall productivity to OSS projects. We first analyze the general structure of the social networks, e.g., graph distances and the degree distribution of the social networks. Our analysis confirms that the social networks of OSS communities follow power-law degree distributions and exhibit small-world characteristics. However, the degree mixing pattern shows that high degree nodes tend to connect more with low degree nodes, suggesting collaborations between experts and newbie developers. Second, we study the correlation between graph degrees and the productivity of the contributors in terms of the amount of contribution and commitment to OSS projects. The analysis demonstrates evident influence of the social ties on the developers' overall productivity.
AB - We conduct a statistical analysis on the social networks of contributors in Open Source Software (OSS) communities using datasets collected from two most fast-growing OSS social interaction sites, Github.com and Ohloh.net. Our goal is to analyze the connectivity structure of the social networks of contributors and to investigate the effect of the different social tie structures on developers' overall productivity to OSS projects. We first analyze the general structure of the social networks, e.g., graph distances and the degree distribution of the social networks. Our analysis confirms that the social networks of OSS communities follow power-law degree distributions and exhibit small-world characteristics. However, the degree mixing pattern shows that high degree nodes tend to connect more with low degree nodes, suggesting collaborations between experts and newbie developers. Second, we study the correlation between graph degrees and the productivity of the contributors in terms of the amount of contribution and commitment to OSS projects. The analysis demonstrates evident influence of the social ties on the developers' overall productivity.
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U2 - 10.1145/2492517.2492627
DO - 10.1145/2492517.2492627
M3 - Conference contribution
AN - SCOPUS:84893239219
SN - 9781450322409
T3 - Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013
SP - 56
EP - 60
BT - Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013
PB - Association for Computing Machinery
T2 - 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2013
Y2 - 25 August 2013 through 28 August 2013
ER -