degree_w: Degree centrality in a weighted network

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

Description

This function calculates two degree measures: the number of contacts that a node is connected to, and the sum of weights on ties originating from a node (out-strength). To calculate the reverse (in-degree, in-strength), specify type="in".

Usage

degree_w(net,measure=c("degree","output"), type="out", alpha=1)

Arguments

net	A weighted edgelist
measure	specifies which measures should be calculated
type	shall out- or in-measures be calculated? Default is out. For undirected networks, this setting is irrelevant, but must be specified.
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 sum of tie weights is used. This measure simply use the tie weights and disregards the number of nodes on the paths.

Value

Returns a data.frame with two or more columns: the first column contains the nodes' ids, and the remaining columns contain the scores of the measures specified in the measure-parameter.

Note

version 1.0.0

Author(s)

Tore Opsahl; http://toreopsahl.com

References

http://toreopsahl.com/2008/11/28/network-weighted-network/

Examples

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

## Run the programme
degree_w(network)

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