This presentation looks at job changes of software developers within an open source software community using
relational predictors of job change activity to model the actions of the actors involved. Interactions with other actors
on mailing lists and in software contributions will be used as predictors.
Open source software is developed in the open where anyone can view the source code and anyone with the knowledge
to do so can contribute to the project. Because people from around the world work on these projects together using
online tools with publicly accessible interactions between people, it is a relevant setting for studying job changes
using Social Network Analysis to understand and model the network relationships between individuals both before
and after a job change.
Network Relationships and Job Changes of Software Developers at Sunbelt 2016
1. Network Relationships and Job Changes of Software Developers
Dawn M. Foster, Guido Conaldi, Riccardo De Vita
Sunbelt XXXVI April 6, 2016
2. The Context
Part of Larger Research Project - PhD Dissertation
• Qualitative: how participants talk about
collaboration
• Network Analysis: quantify collaboration
Research Question for Overall Research Project:
• How do participants who are paid by
organizations collaborate within a community?
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4. Literature on paid developers in open source
• Organizations and individuals devote time and resources to contribute to
public good projects (Grand et al 2004; von Hippel & von Krogh 2003).
• Paid software developers are one way that organizations contribute, and
projects are seeing increased participation from paid developers
(Jensen & Scacchi 2007; Roberts et al. 2006).
• Those who are paid to contribute are often motivated to make more
contributions (Roberts et al. 2006), have a stronger desire to get their
code into the project, and some move into leadership roles (Shah 2006).
• While some researchers emphasize the antagonism between corporate
and community interests (Hars & Ou 2002), others have found benefits
to organizations in open source communities for innovation, knowledge
creation, etc. (Henkel 2006; Mockus et al. 2002).
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5. The Challenge
Open source software is a collaborative effort
People from many organizations work together
Risk of Job Changes (influence)
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6. Research Setting
Linux kernel community*
• Open source software
• Over 85% of contributors are paid
• Neutral: competing companies contribute
• 19M lines of code, 11K developers, 1,200 orgs
6 * Corbet et al., 2015
7. Job Changes
Influence moves with an actor to a new job
Job change data
Activity in code production and mailing list.
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8. Approach: Event History Analysis
Cox Regression Model (Proportional Hazard)
h(t) = h0(t) exp(β’x)
• Hazard function of time
• h0(t) - baseline hazard function
• β’x – covariates that affect hazard rate
• set of x’s - variable of interest over vector of β’s
• For each estimated β, exp(β) gives respective hazard ratio
Pilot: Validate approach with subset of collaboration data
• Future: expand and run model of more complete data set.
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9. Pilot Data
Complete Job Change Data:
• 2006-03-20 through 2015-11-01
• 414 people changed jobs; 661 job changes
Pilot Data: Subset of Mailing List Posts
• Selected 10 of the most widely used mailing lists (240+ lists)
• People with posts from these lists: 195
• Job changes: 239
• Post spells with posts: 80,724
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11. 11
i A
i B
j B
j C
k A
i A
j A
60 days of past mailing list posts
i A
Day 0
Past 30 days
Past 60 days
12. 12
i A
i B
j B
j C
k A
i A
j A
60 days of past mailing list posts: Degree
i A
Day 0
Past 30 days
Past 60 days
13. 13
i A
i B
j B
j C
k A
i A
j A
60 days of past mailing list posts: Two-Path
i A
Day 0
Past 30 days
Past 60 days
14. 14
i A
i B
j B
j C
k A
i A
j A
60 days of past mailing list posts: Four-Cycle
i A
Day 0
Past 30 days
Past 60 days
15. Results and Implications
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Variable exp(coef) Robust SE Significance
Code Commits 0.964546*** 0.010149 (0.000376)
Degree 0.952422 0.025764 (0.058478)
2-Path 1.022684 0.032780 (0.493801)
4-Cycle 0.726703** 0.104016 (0.002147)
Primary Email 0.678074* 0.160710 (0.015632)
N. of observations: 80724
N. of events: 239
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05
16. Limitations and Future Work
More data
Other time windows
Missing covariates
Additional network analysis
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17. Thank You and Questions
Authors:
Dawn M. Foster D.M.Foster@greenwich.ac.uk
@geekygirldawn http://fastwonderblog.com
Guido Conaldi G.Conaldi@greenwich.ac.uk
Riccardo De Vita R.DeVita@greenwich.ac.uk
University of Greenwich, Centre for Business Network Analysis
http://www.gre.ac.uk/business/research/centres/cbna/
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18.
19. References
Corbet, J., Kroah-Hartman, G. & McPherson, A., 2015. Linux Kernel Development: How Fast is it Going,
Who is Doing It, What Are They Doing and Who is Sponsoring the Work, Available at: http://
www.linuxfoundation.org/publications/linux-foundation/who-writes-linux-2015.
Grand, S., von Krogh, G., Leonard, D. & Swap, W., 2004. Resource allocation beyond firm boundaries.
Long Range Planning, 37(6), pp.591–610.
Von Hippel, E. & von Krogh, G., 2003. Open Source Software and the “Private-Collective” Innovation
Model: Issues for Organization Science. Organization science, 14(2), pp.209–223.
Jensen, C. & Scacchi, W., 2007. Role Migration and Advancement Processes in OSSD Projects: A
Comparative Case Study. 29th International Conference on Software Engineering (ICSE’07), pp.364–
374.
Roberts, J., Hann, I. & Slaughter, S., 2006. Understanding the motivations, participation, and performance
of open source software developers: A longitudinal study of the Apache projects. Management science,
52(7), pp.984–999.
Shah, S.K., 2006. Motivation, Governance, and the Viability of Hybrid Forms, in Open Source Software
Development. Management Science, 52(7), pp.1000–1014.
Hars, A. & Ou, S., 2002. Working for free? Motivations of participating in open source projects.
International Journal of Electronic Commerce, 6(3), pp.25–39.
Henkel, J., 2006. Selective revealing in open innovation processes: The case of embedded Linux.
Research Policy, 35, pp.953–969.
Mockus, A., Fielding, R.T. & Herbsleb, J.D., 2002. Two case studies of open source software development:
Apache and Mozilla. ACM Transactions on Software Engineering and Methodology, 11(3), pp.309–346.