scholarly journals CliquePercolation: An R Package for conducting and visualizing results of the clique percolation network community detection algorithm

2021 ◽  
Vol 6 (62) ◽  
pp. 3210
Author(s):  
Jens Lange
Keyword(s):  
Community Detection ◽  
R Package ◽  
Detection Algorithm ◽  
Network Community ◽  
Clique Percolation ◽  
Community Detection Algorithm ◽  
Percolation Network

scholarly journals NCSS: an effective and efficient complex network community detection algorithm

2016 ◽  
Vol 46 (4) ◽  
pp. 431-444
Author(s):  
Zhongming HAN ◽  
Xusheng TAN ◽  
Yan CHEN ◽  
Dagao DUAN
Keyword(s):  
Complex Network ◽  
Community Detection ◽  
Detection Algorithm ◽  
Network Community ◽  
Community Detection Algorithm

scholarly journals The ComDet Package - Iterated Community Detection for the Analysis of Community Membership, its Stability and the Detection of Fuzzy Community Boundaries.

2018 ◽  
Author(s):  
Marlene Werner
Keyword(s):  
Community Detection ◽  
Network Models ◽  
R Package ◽  
Detection Algorithm ◽  
Technical Note ◽  
Detection Algorithms ◽  
Community Boundaries ◽  
Prior Literature ◽  
Community Detection Algorithm ◽  
The Stability

In recent years, network analysis has entered psychological science. In psychological network models, nodes are variables and edges are estimated relationships between these variables. In this project, we answer recent calls for the use of established network community detection algorithms to detect clusters in psychological networks. This technical note introduces the ComDet package (under development for use in R), a package aimed at extending the functionality of the commonly used non-deterministic community detection algorithm spinglass. ComDet repeatedly performs the spinglass community detection algorithm (based on the igraph package in R) for a specified number of runs, quantifies and summarizes the results across runs, and visualizes those results. Our extended community detection function builds upon the prior literature in two ways. First, it offers summarizing output that communicates the stability and variability of particular community results. Second, because this package is implemented in R, the same platform commonly used to assess psychological networks, it can be readily applied as part of the growing toolbox for assessing psychological networks. This technical note will be updated with new insights in the near future. The final aim of this project is to provide researchers with a freely available R-package that runs the ComDet function using spinglass and, potentially, other non-deterministic community detection algorithms.

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