Abstract
We conduct an extensive 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 ties 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 social network structure analysis confirms a power-law degree distribution and small-world characteristics. However, the degree mixing pattern shows that high degree nodes tend to connect more with low degree nodes suggesting a collaboration between experts and newbie developers. We further conduct the same analysis on affiliation networks and find that contributors tend to participate in projects of similar team sizes. Second, we study the correlation between various social factors (e.g., closeness and betweenness centrality, clustering coefficient and tie strength) and the productivity of the contributors in terms of the amount of contribution and commitment to OSS projects. The analysis is conducted under the contexts of global and local networks, where a global network analysis considers a developer’s connectivity in the whole OSS community network, whereas a local network analysis considers a developer’s connectivity within a team network that is affiliated to a project. The analysis demonstrates evident influence of the social factors on the developers’ overall productivity.
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Notes
- 1.
We decided to have a threshold of two units of link weights to distinguish the weak ties from the strong ties because participants follow power low distribution [10] and most OSS projects have one to two participants.
- 2.
The commits log is collected by Ohloh.net and Github.com.
References
Antwerp MV, Madey GR (2010) The importance of social network structure in the open source software developer community. In: HICSS, IEEE Comput Soc, pp 1–10
Backstrom L, Huttenlocher D, Kleinberg J, Lan X (2006) Group formation in large social networks: membership, growth, and evolution. In: Proceedings of the 12th ACM SIGKDD international conference on knowledge discovery and data mining, KDD ’06, ACM, New York, pp 44–54
Bird C, Pattison D, D’Souza R, Filkov V, Devanbu P (2008) Latent social structure in open source projects. In: Proceedings of the 16th ACM SIGSOFT international symposium on foundations of software engineering. SIGSOFT ’08/FSE-16, ACM, New York , pp 24–35
Casaló LV, Cisneros J, Flavián C, Guinaliu M (2009) Determinants of success in open source software networks. Ind Manage Data Syst 109(4):532–549
Crowston K, Howison J (2003) The social structure of open source software development teams. First monday, 10(2)
Garousi V (2009) Investigating the success factors of open-source software projects across their lifetime. J Software Eng Stud 4:115
Hahn J, Moon JY, Zhang C (2008) Emergence of new project teams from open source software developer networks: impact of prior collaboration ties. Informa Syst Res 19(3):369–391
Hertel G, Niedner S, Herrmann S (2003) Motivation of software developers in open source projects: an internet-based survey of contributors to the Linux Kernel. Res Policy 32(7):1159–1177
Lee S-YT, Kim H-W, Gupta S (2009) Measuring open source software success. Omega 37(2):426–438
Madey G, Freeh V, Tynan R (2002) The open source software development phenomenon: an analysis based on social network theory. In: Proceedings of the Americas conference on information systems (AMCIS 2002), Dallas, Texas, pp 1806–1813
Mahadevan P, Krioukov D, Fall K, Vahdat A (2006) Systematic topology analysis and generation using degree correlations. In: Proceedings of the 2006 conference on applications, technologies, architectures, and protocols for computer communications, SIGCOMM ’06, ACM, New York, pp 135–146
Michlmayr M, Hill BM (2003) Quality and the reliance on individuals in free software projects. In: Proceedings of the 3rd workshop on open source software engineering, Portland, Oregon, pp 105–109
Milgram S (1967) The small world problem. Psychol Today 61:60–67
Mislove A, Marcon M, Gummadi KP, Druschel P, Bhattacharjee B (2007) Measurement and analysis of online social networks. In: Proceedings of the 7th ACM SIGCOMM conference on Internet measurement. IMC ’07, ACM, New York, pp 29–42
Newman MEJ (2003) Mixing patterns in networks. PRE 67(2):026126
Robles G, Gonzalez-Barahona JM, Michlmayr M ( 2005) Evolution of volunteer participation in libre software projects: evidence from Debian. In: Proceedings of the first international conference on open source systems, Genova, Italy, pp 100–107
Samoladas I, Gousios G, Spinellis D, Stamelos I (2008) The sqo-oss quality model: measurement based open source software evaluation. In: OSS, pp 237–248
Subramaniam C, Sen R, Nelson ML (2009) Determinants of open source software project success: a longitudinal study. Decis Support Syst 46(2):576–585
Surian D, Lo D, Lim E-P (2010) Mining collaboration patterns from a large developer network. In: Antoniol G, Pinzger M, Chikofsky EJ (eds) WCRE, IEEE Comput Soc, pp 269–273
Wu J, Goh K-Y (2009) Evaluating longitudinal success of open source software projects: a social network perspective. In: HICSS, pp 1–10
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Allaho, M.Y., Lee, WC. (2015). Analyzing the Social Networks of Contributors in Open Source Software Community. In: Kazienko, P., Chawla, N. (eds) Applications of Social Media and Social Network Analysis. Lecture Notes in Social Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-19003-7_4
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