betweenness_w: Betweenness centrality in a weighted network

In tnet: Weighted, Two-Mode, and Longitudinal Networks Analysis

Description

This function calculates betweenness scores for nodes in a weighted network based on the distance_w-function.
Note: This algorithm relies on the igraphs package's implementation of Dijkstra's algorithm. Currently, it does not find multiple shortest paths if two exist.

Usage

 betweenness_w(net, directed=NULL, alpha=1) 

Arguments

net	A weighted edgelist
directed	logical, whether the network is directed or undirected. Default is NULL, this means that the function checks whether the edgelist is directed or not.
alpha	sets the alpha parameter in the generalised measures from Opsahl, T., Agneessens, F., Skvoretz, J., 2010. Node Centrality in Weighted Networks: Generalizing Degree and Shortest Paths. Social Networks. If this parameter is set to 1 (default), the Dijkstra shortest paths are used. The length of these paths rely simply on the tie weights and disregards the number of nodes on the paths.

Value

Returns a data.frame with two columns: the first column contains the nodes' ids, and the second column contains the nodes' betweenness scores.

Note

version 1.0.0

Author(s)

Tore Opsahl; http://toreopsahl.com

References

http://toreopsahl.com/2009/02/20/betweenness-in-weighted-networks/

Examples

## Load sample data
sampledata <- rbind(
c(1,2,1),
c(1,3,5),
c(2,1,1),
c(2,4,6),
c(3,1,5),
c(3,4,10),
c(4,2,6),
c(4,3,10))

## Run the programme
betweenness_w(sampledata)

tnet documentation built on Feb. 25, 2020, 1:07 a.m.