Managing the boundary of an 'open' project

In the past ten years, the boundaries between public and open science and commercial research efforts have become more porous. Scholars have thus more critically examined ways in which these two institutional regimes intersect. Large open source software projects have also attracted commercial collaborators and now struggle to develop code in an open public environment that still protects their communal boundaries. This research applies a dynamic social network approach to understand how one community-managed software project, Debian, developed a membership process. We examine the project's face-to-face social network over a five-year period (1997-2001) to see how changes in the social structure affected the evolution of membership mechanisms and the determination of gatekeepers. While the amount and importance of a contributor's work increased the probability that a contributor would become a gatekeeper, those more central in the social network were more likely to become gatekeepers and influence the membership process. A greater understanding of the mechanisms open projects use to manage their boundaries has critical implications for research and knowledge-producing communities operating in pluralistic, open and distributed environments.open source software; social networks; organizational design; institutional design;

HOW MICROBLOG FOLLOWER NETWORKS AFFECT OPEN SOURCE SOFTWARE PROJECT SUCCESS

Successful open source software (OSS) projects require efficient communication means and a steady supply of voluntary developers. Microblogging, as well as the follower network it generates, is becoming increasingly popular as an emerging Web 2.0 communication technology in many online OSS communities. However, little is known about how microblogging follower networks affect OSS project success. Based on theories drawn from the social network domain, OSS and virtual team research,we hypothesized two follower network mechanisms – preferential attachment and structural holes – which may significantly affect OSS project success, by improving knowledge sharing and attracting more skillful developers. We plan to empirically study a microblog follower network in a large online OSS community, aiming to examine the impacts of the two hypothesized follower network mechanisms on OSS project success. Our potential findings may provide insights for OSS project managers to better manage microblog communications and thereby achieve project success

Can we avoid high coupling?

It is considered good software design practice to organize source code into modules and to favour within-module connections (cohesion) over between-module connections (coupling), leading to the oft-repeated maxim "low coupling/high cohesion". Prior research into network theory and its application to software systems has found evidence that many important properties in real software systems exhibit approximately scale-free structure, including coupling; researchers have claimed that such scale-free structures are ubiquitous. This implies that high coupling must be unavoidable, statistically speaking, apparently contradicting standard ideas about software structure. We present a model that leads to the simple predictions that approximately scale-free structures ought to arise both for between-module connectivity and overall connectivity, and not as the result of poor design or optimization shortcuts. These predictions are borne out by our large-scale empirical study. Hence we conclude that high coupling is not avoidable--and that this is in fact quite reasonable

Discovering Determinants of Project Participation in an Open Source Social Network

Successful open source software projects often require a steady supply of self motivated software developers. However, little work has been done from a relational/network perspective to study the factors that drive the developers to participate in OSS projects. In this paper, we investigate the participation dynamics in a social network, particularly in an online open source community called Ohloh. Through a REST-based API, we collected information about 11,530 open source software projects involving 94,330 developers. Using social network analysis and statistical analysis methods, we examine a set of social and technical factors in the Ohloh dataset, which we define as the determinants that significantly influence the developers’ participation choices. We found that the determinants include (1)homophily in programming language, (2)project mutual acquaintance, and (3)project age. In addition, our research findings provide the possibility of predicting developers’ participation choices based on the discovered determinants, and therefore can have important implications for OSS project management and in designing social network enabled recommendation systems

Collaboration in scientific digital ecosystems: A socio-technical network analysis

This dissertation seeks to understand the formation, operation, organizational (collaboration) and the effect of scientific digital ecosystems that connect several online community networks in a single platform. The formation, mechanism and processes of online networks that influence members output is limited and contradictory. The dissertation is comprised of three papers that are guided by the following research questions: How does online community member’s productivity (or success) depend upon their ‘position’ in the digital networks? What are the network formation mechanism, structures and characteristics of an online community? How do scientific innovations traverse (diffuse) amongst users in online communities? A combination of exploratory, inductive and deductive research designs is applied sequentially but in a non-linear manner to address research question. The dissertation contributes to the literature on scientific collaboration, digital communities of creation, social network modelling and diffusion of innovation. The first paper applies network theory and spatial probit autocorrelative modelling technique to evaluate how member developer’s positioning in digital community correlate with his/her productivity. The second paper looks at the dynamics of developer’s participation in online developers’ network for a period spanning 7-years using exponential random graph models (ERGM). This paper applies theory of network (network science) to model network formation patterns in developer community. The third paper, like the first, applies network theory and to understand user network characteristics and communication channels which influence diffusion of scientific innovations. Bass and spatial probit autocorrelative models are applied for this analysis. Data from this study was mined from developers, authors and user communities of nanoHUB.org cyberinfrastructure platform. NanoHUB.org is a science and engineering online ecosystem comprising self-organized researchers, educators, and professional communities in eight member institutions that collaborate, share resources and solve nanotechnology related problems including development and usage of tools (scientific innovation). Data from collaboration and information sharing activities was used to create the developers, authors and user networks that were used for analysis. Results of the first paper show that the spatial autocorrelation parameter of the spatial probit model is negative and statistically different from zero. The negative spatial spillover effect in the developer network imply that developers that are embedded in the network have a lower probability of getting more output. The structural network characteristics of eigen vector centrality had statistically significant effects on probability of being more productive. Developers who are also authors were found to be more productive than those in one network. The implications of these findings is that developers will benefit from being in multiple network spaces and by associating with more accomplished developers. The autocorrelative and interaction models also reveal various new modelling approach of accounting for network autocorrelation effects to online member. Results of the second paper show that developers form in a manner that follow a pure uniform random distribution. Results also show that developer’s collaborative mechanisms are characterized by low tendencies to reciprocate and form homophiles (tendency of developers to associate with similar peers) but high tendency to form clusters. The implications of network formation mechanism and processes are that developers are forming in a purely random and self-organized manner and minimum efforts should be applied in trying to organize and influence the community organization. The results also reveal that a simple link to link ERGM and stochastic dominance criteria can be combined to characterize the network formation characteristics just like the ERG(p*) model but have an advantage of overcoming degeneracy challenges associated with ERG(p*) models. Results of the third paper show that bass model is a good predictor for diffusion of scientific innovations (tools) in online community setting. Results also show different innovations have varying levels and rates of adoption and these were influenced by both external and internal factors. Results of the micro-based model found degrees and betweeness centrality as some of the internal variables that have positive influence on the adoption of innovation while centrality measures of power or leadership were found to have negative influence of adoption process. The relative time taken to run a simulation (measured as job usage time) was also found to be negatively influencing diffusion. The implication of the study results is that bass model is a good fit for evaluating and forecasting adoption of innovation in online communities. Moreover, network structural characteristics are responsible for adoption of innovation adoption and policy making should consider tool adoption enhancing ones. Additionally, researchers could further explore the network structural characteristics that are driving diffusion of innovation

The Open Source Software Ecosystem

[first paragraph] Open source research in the late 1990s and early 2000\u27s described open source development projects as all-volunteer endeavors without the existence of monetary incentives (Chakravarty, Haruvy and Wu, 2007), and relatively recent empirical studies (Ghosh, 2005; Wolf {{243}}) confirm that a sizable percentage of open source developers are indeed volunteers.1 Open source development projects involving more than one developer were seen to follow a “hacker ethic” (Himanen, 2000; von Hippel and von Krogh, 2003) where individuals freely give away and exchange software they had written so that it could be modified and built upon, with an expectation of reciprocation. An early puzzle, of particular interest to economists, was why people would voluntarily contribute their ideas and time to these projects (Lerner and Tirole {{243}}. We\u27ll focus on these fine-scale behavioral questions in Chapter 3, and will explain that there are clear reasons – such as distance learning, signaling, enjoyment, and “user-driven innovation” based on a need (von Hippel, 2005) – that motivate these volunteers to participate