Who connects with whom? A social network analysis of an online open source software community

First Monday ◽  
2011 ◽  
Author(s):  
Cuihua Shen ◽  
Peter Monge
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Online Community ◽  
Online Social Network ◽  
The Social ◽  
Collaboration Dynamics ◽  
The Web

By examining “who connects with whom” in an online community using social network analysis, this study tests the social drivers that shape the collaboration dynamics among a group of participants from SourceForge, the largest open source community on the Web. The formation of the online social network was explored by testing two distinct network attachment logics: strategic selection and homophily. Both logics received some support. Taken together, the results are suggestive of a “performance-based clustering” phenomenon within the OSS online community in which most collaborations involve accomplished developers, and novice developers tend to partner with less accomplished and less experienced peers.

scholarly journals Social Network Analysis Visualization

2015 ◽  
pp. 257-270
Author(s):  
Mohana Shanmugam ◽  
Yusmadi Yah Jusoh ◽  
Rozi Nor Haizan Nor ◽  
Marzanah A. Jabar
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Social Network ◽  
Future Research ◽  
Research Gaps ◽  
The Social ◽  
Network Studies ◽  
Academic Study

The social network surge has become a mainstream subject of academic study in a myriad of disciplines. This chapter posits the social network literature by highlighting the terminologies of social networks and details the types of tools and methodologies used in prior studies. The list is supplemented by identifying the research gaps for future research of interest to both academics and practitioners. Additionally, the case of Facebook is used to study the elements of a social network analysis. This chapter also highlights past validated models with regards to social networks which are deemed significant for online social network studies. Furthermore, this chapter seeks to enlighten our knowledge on social network analysis and tap into the social network capabilities.

Using Social Network Analysis to Guide Theoretical Sampling in an Ethnographic Study of a Virtual Community

2011 ◽  
pp. 157-174 ◽  
Author(s):  
Enrique Murillo
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Communities ◽  
Online Community ◽  
Virtual Community ◽  
Ethnographic Study ◽  
Qualitative Studies ◽  
The Social ◽  
Theoretical Sampling

Social Network Analysis (SNA) provides a range of models particularly well suited for mapping bonds between participants in online communities and thus reveal prominent members or subgroups. This can yield valuable insights for selecting a theoretical sample of participants or participant interactions in qualitative studies of communities. This chapter describes a procedure for collecting data from Usenet newsgroups, deriving the social network created by participant interaction, and importing this relational data into SNA software, where various cohesion models can be applied. The technique is exemplified by performing a longitudinal core periphery analysis of a specific newsgroup, which identified core members and provided clear evidence of a stable online community. Discussions dominated by core members are identified next, to guide theoretical sampling of text-based interactions in an ongoing ethnography of the community.

Finding Influential Nodes in Sourceforge.net Using Social Network Analysis

2021 ◽  
pp. 156-166
Author(s):  
K.G. Srinivasa ◽  
Ganesh Chandra Deka ◽  
Krishnaraj P.M.
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Open Source ◽  
Information Flow ◽  
Open Source Software ◽  
Small Set ◽  
Influential Nodes

The contribution of volunteers in the development of Free and Open Source Software in Sourceforge.net is studied in this paper. Using Social Network analysis, the small set of developers who can maximize the information flow in the network are discovered. The propagation of top developers across past three years are also studied. The four algorithms used to find top influential developers gives almost similar results. The movement of top developers over past years years was also consistent.

Finding Influential Nodes in Sourceforge.net Using Social Network Analysis

2018 ◽  
pp. 104-116
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Open Source ◽  
Information Flow ◽  
Open Source Software ◽  
Small Set ◽  
Influential Nodes

The contribution of volunteers in the development of Free and Open Source Software in Sourceforge.net is studied in this paper. Using Social Network analysis, the small set of developers who can maximize the information flow in the network are discovered. The propagation of top developers across past three years are also studied. The four algorithms used to find top influential developers gives almost similar results. The movement of top developers over past years years was also consistent.

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