@article {Singh:2010:SEI:1824760.1824763,
	title = {The small-world effect: The influence of macro-level properties of developer collaboration networks on open-source project success},
	journal = {ACM Trans. Softw. Eng. Methodol.},
	volume = {20},
	number = {2},
	year = {2010},
	pages = {6:1{\textendash}6:27},
	publisher = {ACM},
	address = {New York, NY, USA},
	abstract = {In this study we investigate the impact of community-level networks{\textemdash}relationships that exist among developers in an OSS community{\textemdash}on the productivity of member developers. Specifically, we argue that OSS community networks characterized by small-world properties would positively influence the productivity of the member developers by providing them with speedy and reliable access to more quantity and variety of information and knowledge resources. Specific hypotheses are developed and tested using longitudinal data on a large panel of 4,279 projects from 15 different OSS communities hosted at Sourceforge. Our results suggest that significant variation exists in small-world properties of OSS communities at Sourceforge. After accounting for project, foundry, and time-specific observed and unobserved effects, we found a statistically significant relationship between small-world properties of a community and the technical and commercial success of the software produced by its members. In contrast to the findings of prior research, we also found the lack of a significant relationship between closeness and betweenness centralities of the project teams and their success. These results were robust to a number of controls and model specifications.},
	keywords = {collaborative software development, online community, open source software development, productivity, small world networks, social networks, sourceforge, team formation},
	issn = {1049-331X},
	doi = {10.1145/1824760.1824763},
	url = {http://doi.acm.org/10.1145/1824760.1824763},
	author = {Param Vir Singh}
}
@article {flosswp327,
	title = {An Empirical Investigation of Code Contribution, Communication Participation and Release Strategies in Open Source Software Development: A Conditional Hazard Model Approach},
	year = {2007},
	month = {January},
	abstract = {This study uses data from over 200 open source software (OSS) projects hosted at Sourceforge to empirically examine how OSS development characteristics affect project progress. Consistent with prior studies, we find that core developers (i.e., top 20 \% of the most contributing developers) develop about 80\% of the code. We also find that a group of developers that is about 50\% larger than the core group is responsible for 80\% of the communication. On average, the top 30\% developers contribute about 81\% of the messages. It is observed that projects with a clearly identified core group of developers conducting most of the coding are more efficient for project progress. We also find that highly participative peripheral group in communication positively affects project progress. In addition, high level of communication interactivity, measured by the number of email threads and average thread depth, enables a project to progress well. Our results also show that projects that draw upon the larger OSS community for beta testing progress faster. We find that the projects that do not progress well are associated with the following major factors: (i) lack of a core developer group, (ii) dormant peripheral group in communication, (iii) low communication interactivity exemplified by the lack of depth in threaded communications, and (iv) over-dependence on internal community for beta testing.},
	attachments = {https://flosshub.org/sites/flosshub.org/files/singh_fan_tan.pdf},
	author = {Param Vir Singh and Ming Fan and Yong Tan}
}
@proceedings {136,
	title = {Open source software development and the small world phenomenon: an empirical investigations of macro level colaboration network properties on project success},
	year = {2007},
	keywords = {NotreDameArchive},
	author = {Param Vir Singh}
}
@proceedings {144,
	title = {Social capital, structural holes and team composition: collaborative networks of the open source software community},
	year = {2007},
	keywords = {NotreDameArchive},
	author = {Yong Tan and Vijay Mookerjee and Param Vir Singh}
}
@article {flosswp322,
	title = {Developer Learning Dynamics in Open Source Software Projects: A Hidden Markov Model Analysis},
	year = {2006},
	month = {December},
	abstract = {This work proposes a dynamic model of developer learning in open source software (OSS) projects. A Hidden Markov Model (HMM) is proposed to explain how the code contribution behaviors of OSS de-velopers change as their levels of knowledge on their projects increase. In this model, discrete hidden states represent the unobserved knowledge levels of developers, and their observed code contribution be-haviors are modeled as state dependent. Developers??? knowledge levels evolve as they learn about the pro-jects over time. Two modes of learning are considered: learning-by-doing (code development) and learn-ing through interactions with peers. The model is calibrated using data spanning six years for 25 OSS pro-jects and 251 developers hosted at Sourceforge. The proposed model identifies three knowledge states (high, medium, and low) and estimates the impact of the two modes of learning on the transition of devel-opers between the three knowledge states. The model results suggest that in the low knowledge state de-velopers exhibit the greatest inertia, followed by those in the medium and high states. Both modes of learning are found to have varying impact across the three knowledge states. Interactions with peers ap-pear to be an important source of learning for developers in all states. A developer in the low state learns only through participation in threads started by others. Prior code contribution and starting discussion by initiating threads do not impact the knowledge level of a developer in the low state. Initiating threads, par-ticipating in threads started by others, and prior code contributions have positive impacts on the knowl-edge level of a developer in the medium or high state and, hence, influence his long term code contribu-tion behavior. Explanations for these varying impacts of learning activities on the transitions of develop-ers between the three states are provided. We also find a lack of persistence of knowledge in all states. The HMM better describes the data than a latent class model which would suggests that the learning ac-tivities have a long term, dynamic impact, rather than an immediate, static impact on the code contribu-tion behavior of a developer.},
	attachments = {https://flosshub.org/sites/flosshub.org/files/singh-youn-tan.pdf},
	author = {Param Vir Singh and Nara Youn and Yong Tan}
}
