computeTMDegree: Compute Degree Centrality Values for Two-Mode Networks
In dream: Dynamic Relational Event Analysis and Modeling

computeTMDegree

R Documentation

Compute Degree Centrality Values for Two-Mode Networks

Description

This function computes the degree centrality values for two-mode networks following Knoke and Yang (2020). The computed degree centrality is based on the specified level. That is, in an affiliation matrix, the density can be computed on the symmetric g x g co-membership matrix of level 1 actors (e.g., medical doctors) or on the symmetric h x h shared actors matrix for level 2 groups (e.g., hospitals) based on their shared members.

Usage

computeTMDegree(net, level1 = TRUE)

Arguments

`net`	A two-mode adjacency matrix
`level1`	TRUE/FALSE. TRUE indicates that the degree centrality will be computed for level 1 nodes. FALSE indicates that the degree centrality will be computed for level 2 nodes. Set to TRUE by default.

Details

Following Knoke and Yang (2020), the computation of degree for two-mode affiliation networks is level specific. A two-mode affiliation matrix X with dimensions g x h, where g is the number of level 1 nodes (e.g., medical doctors) and h is the number of level 2 nodes (i.e., hospitals). If the function is defined on the level 1 nodes, the degree centrality of an actor i is computed as:

X^{G} = XX^{T}

C_{D}^{G}(g_{i}) = \sum_{i = 1}^{g} x_{ij}^{g} \quad (i \neq j)

In contrast, if it is defined on the level 2 nodes, the degree centrality of an actor i is computed as:

X^{H} = X^{T}X

C_{D}^{H}(h_{i}) = \sum_{i = 1}^{h} x_{ij}^{h} \quad (i \neq j)

Value

The vector of two-mode level-specific degree centrality values.

Author(s)

Kevin A. Carson kacarson@arizona.edu, Diego F. Leal dflc@arizona.edu

References

Knoke, David and Song Yang. 2020. Social Network Analysis. Sage: Quantitative Applications in the Social Sciences (154)

Examples

#Replicating the biparitate graph presented in Knoke and Yang (2020: 109)
knoke_yang_PC <- matrix(c(1,1,0,0, 1,1,0,0,
                          1,1,1,0, 0,0,1,1,
                          0,0,1,1), byrow = TRUE,
                          nrow = 5, ncol = 4)
colnames(knoke_yang_PC) <- c("Rubio-R","McConnell-R", "Reid-D", "Sanders-D")
rownames(knoke_yang_PC) <- c("UPS", "MS", "HD", "SEU", "ANA")
computeTMDegree(knoke_yang_PC, level1 = TRUE) #this value matches the book
computeTMDegree(knoke_yang_PC, level1 = FALSE) #this value matches the book

dream documentation built on Aug. 8, 2025, 6:36 p.m.