degree {sna} | R Documentation |
Degree
takes a graph stack (dat
) and returns the degree centralities of positions within one graph (indicated by nodes
and g
, respectively). Depending on the specified mode, indegree, outdegree, or total (Freeman) degree will be returned; this function is compatible with centralization
, and will return the theoretical maximum absolute deviation (from maximum) conditional on size (which is used by centralization
to normalize the observed centralization score).
degree(dat, g=1, nodes=c(1:dim(dat)[2]), gmode="digraph", diag=FALSE, tmaxdev=FALSE, cmode="freeman", rescale=FALSE)
dat |
Data array to be analyzed. By assumption, the first dimension of the array indexes the graph, with the next two indexing the actors. Provided that FUN is well-behaved, this can be an n x n matrix if only one graph is involved. |
g |
Integer indicating the index of the graph for which centralities are to be calculated. By default, g==1 . |
nodes |
List indicating which nodes are to be included in the calculation. By default, all nodes are included. |
gmode |
String indicating the type of graph being evaluated. "digraph" indicates that edges should be interpreted as directed; "graph" indicates that edges are undirected. gmode is set to "digraph" by default. |
diag |
Boolean indicating whether or not the diagonal should be treated as valid data. Set this true if and only if the data can contain loops. diag is FALSE by default. |
tmaxdev |
Boolean indicating whether or not the theoretical maximum absolute deviation from the maximum nodal centrality should be returned. By default, tmaxdev==FALSE . |
cmode |
String indicating the type of degree centrality being computed. "indegree", "outdegree", and "freeman" refer to the indegree, outdegree, and total (Freeman) degree measures, respectively. The default for cmode is "freeman". |
rescale |
If true, centrality scores are rescaled such that they sum to 1. |
Degree centrality is the social networker's term for various permutations of the graph theoretic notion of vertex degree: indegree of a vertex, v, corresponds to the cardinality of the vertex set N^+(v) = {i in V(G) : (i,v) in E(G)}; outdegree corresponds to the cardinality of the vertex set N^-(v) = {i in V(G) : (v,i) in E(G)}; and total (or "Freeman") degree corresponds to |N^+(v)|+|N^-(v)|. (Note that, for simple graphs, indegree=outdegree=total degree/2.) Obviously, degree centrality can be interpreted in terms of the sizes of actors' neighborhoods within the larger structure. See the references below for more details.
A vector containing the degree centrality scores
Carter T. Butts buttsc@uci.edu
Freeman, L.C. (1979). ``Centrality in Social Networks I: Conceptual Clarification.'' Social Networks, 1, 215-239.
#Create a random directed graph dat<-rgraph(10) #Find the indegrees, outdegrees, and total degrees degree(dat,cmode="indegree") degree(dat,cmode="outdegree") degree(dat)