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.

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.

Graph Mining Approaches to Study Volunteer Relationships in Sourceforge.net

2018 ◽  
pp. 117-139
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Information Flow ◽  
Graph Mining ◽  
Seed Set ◽  
Number Of Clusters ◽  
Small Set ◽  
Approaches To Study ◽  
Influential Nodes ◽  
Entire Network

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 was also consistent. Influential nodes in a network are very important to diffuse influence on the rest of the network. They are most often highly connected within the network. The existing algorithms are efficient to identify them. However, the challenge is in selecting a seed set that can spread the influence instantaneously with least effort. In this paper, a method is defined to spread influence on the entire network by selecting the least number of non-overlapping influential nodes faster than a well known existing algorithm. Further to this, the number of clusters in the network is also determined simultaneously from the seed set of the networks.

Sign in / Sign up

Export Citation Format

Share Document