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

Quality in peer production systems – impact of assortativity of communication networks on group efficacy

Many online peer production systems (e.g. Wikipedia or Open Source Software communities) strive to deliver high quality intellectual goods that could compare with commercial products. While quality is key to the communities’ success – widespread adoption of their products – it is not clear what makes some succeed, while others provide subpar outcomes or fail entirely. Quality of Wikipedia articles has been previously related to the number of editors writing them or to the diversity of editors’ competences. Here we tested the hypothesis that cohesiveness of private communication networks within collaborating groups increases the quality of their products. We analyzed communication within a sample of Wikiprojects on the English Wikipedia – groups of editors that coordinate their activities to improve articles related to a specific topic. We found that most Wikiprojects communicate in a highly hierarchical, disassortative way, but the successful ones break this trend and their communication networks are structured in a more egalitarian way

Professional development and human resources management in networks

Social networks occupy more places in development of people and organizations. Confidence in institutions and social networking are different and based on referentiality in Internet. For communication in network persons choose a different strategies and behavior in LinkedIn, resources of whom may be in different degree are interesting in Human Resources Management for organizations. Members of different social groups and cultures demonstrate some differences in interaction with Russian identity native. There are gender differences behavior in networks. Participating in groups need ethical behavior and norms in social networking for professional development and communication in future

Three essays on problem-solving in collaborative open productions

The term “open production” is frequently used to describe production systems that rely on volunteer participants who are willing to participate, produce, and bear private costs in order to provide a public good. Examples of open production are becoming increasingly common in many industries. What make these productions possible? How may they be sustained in a world of organizations in which the evolutionary products of economic selection are elaborate hierarchical forms of organization? One way to address these questions is to look at how open productions solve problems that are common to all production organizations such as, for example, problems in the division of labor, allocation of tasks, collaboration, coordination, and maintaining balance between inducement and contributions. Under the conditions of extreme decentralization that are the defining feature of open productions, this approach implies a detailed observation of individual problem solving practices. This is the approach I develop in my dissertation. Unlike much of the prior literature on open productions, I deemphasize motivational elements, status-seeking motives, and allocation of property rights issues. I focus instead on actual work practices as revealed by the day-by-day problem solving activities that qualify open productions projects as production organizations despite the absence of formal contractual arrangements to regulate principal-agent relations. What my work adds to the extensive, informative, and well-developed discipline-based explanations that are currently available, is a focus on the emergence of micro-organizational mechanisms through which problem assignment (Chapter 2), problem resolution (Chapter 3), and sustained participation (Chapter 4) are obtained in open productions. In my essays, I draw from organizational sociology and the behavioral theory of the firm to specify models that relate individual problem-solving activities to structured patterns of action through emergent work practices. In the models that I specify and test, I emphasize processes of attention allocation (Chapter 2), repeated collaboration and group diversity (Chapter 3) and identity construction (Chapter 4) as central to our understanding of the dynamics of problem-solving in organizations. One element of novelty in my study is that my research design makes these work practices directly observable at a level of detail, completeness, and precision that was inaccessible in the past. To illustrate the empirical value of the view that I develop I examine problem-solving activities – i.e., bug fixing and code production – within two Free/Open Source Software (F/OSS) projects during their entire life span. Readers of my work will know more about how organizational micro-mechanisms emerge in open productions

Generation Z and Attending Traditional Spectator Sports: A Study of Contemporary Sport Consumer Behaviour

Understanding consumer behaviour and attracting new generations of consumers are important aspects of operating a successful sport organization (Teed et al., 2008). However, limited academic attention has been given to the most recently emergent generation: Generation Z (Gen Z). Moreover, it has been shown that the interest level in traditional spectator sports is waning amongst younger consumers (Richelieu & Pons, 2005; 2009) and, most recently, Gen Z (Kuchefski, 2018; Whistle, 2018). The purpose of this research was therefore to better understand the sport consumption behaviours of this Gen Z by examining both the motivators and inhibitors to their nominal spectator sport consumption. Participants (n=17) were recruited physically in Hamilton, Ontario and virtually through social media platforms Facebook, Twitter, and LinkedIn. Using a semi-structured format, a total of three synchronous online focus group interviews were conducted with individuals from Gen Z. It was clear from a thorough analysis of the data that participants viewed the consumption of traditional spectator sports analogously with attending live games. Thus, the data, its themes, and its implications were inherently linked to attending traditional spectator sports. Although there were important intragroup differences found, several important motivators and inhibitors were present. Socialization, status, and experimental behaviours all presented as significant motives for Gen Z to attend traditional spectator sports. Alternatively, issues with affordability and a shared unrest proved to be important inhibitors to nominal spectator sport consumption. Directions for future research and recommendations are presented and discussed

Reviewing the Contributing Factors and Benefits of Distributed Collaboration

Distributed collaboration has become increasingly common across domains ranging from software development to information processing, the creative arts, and entertainment. As of early 2020, distributed collaboration has entered the limelight as the COVID-19 pandemic has forced employees across the world to work from home. However, while researchers have applied myriad terms to define these operations, we first address this issue by defining distributed collaboration in a way that represents all its forms. Existing research has identified several factors that contribute to distributed collaborations’ success. Yet, researchers and practitioners typically discuss these factors in modular theoretical terms, which means that they often struggle to identify and synthesize literature that spans multiple domains and perspectives. In this paper, we systematically review the literature to synthesize core findings into one amalgamated model. This model categorizes the contributing factors for distributed collaboration along two axes 1) whether they are social or material and 2) whether they are endemic or relational. We also explicitly discuss the relationships between factors in the model. The model further links these contributing factors to different collaborative outcomes, specifically mutual learning, relationship building, communication, task completion speed, access to skilled personnel, and cost savings

Realizing the Activation Potential of Online Communities

Online communities suffer from the 1-9-90 principle, which states that 1% of the community\u27s user base generates original content, an additional 9% is limited to interacting with existing content, while the remaining 90% of the participants is passively lurking. In this work we present a data-driven stochastic framework that estimates (1) the activation potential (i.e., the users that are currently lurkers but present a high likelihood of becoming heavy contributors) of an online community and (2) when and which users are more likely to become heavy contributors. Our proposed framework captures the transitional evolution of a user by a Hidden Markov Model, and estimates each user\u27s propensity to become a heavy contributor by employing parametric survival models. We build and evaluate our models on a unique large dataset of a specialized online community about diabetes