# constraint: Burt's constraint

Description Usage Arguments Details Value Author(s) References Examples

### Description

Given a graph, `constraint` calculates Burt's constraint for each vertex.

### Usage

 `1` ```constraint(graph, nodes = V(graph), weights = NULL) ```

### Arguments

 `graph` A graph object, the input graph. `nodes` The vertices for which the constraint will be calculated. Defaults to all vertices. `weights` The weights of the edges. If this is `NULL` and there is a `weight` edge attribute this is used. If there is no such edge attribute all edges will have the same weight.

### Details

Burt's constraint is higher if ego has less, or mutually stronger related (i.e. more redundant) contacts. Burt's measure of constraint, C[i], of vertex i's ego network V[i], is defined for directed and valued graphs,

C[i] = sum( [sum( p[i,j] + p[i,q] p[q,j], q in V[i], q != i,j )]^2, j in V[i], j != i).

for a graph of order (ie. number of vertices) N, where proportional tie strengths are defined as

p[i,j]=(a[i,j]+a[j,i]) / sum(a[i,k]+a[k,i], k in V[i], k != i),

a[i,j] are elements of A and the latter being the graph adjacency matrix. For isolated vertices, constraint is undefined.

### Value

A numeric vector of constraint scores

### Author(s)

Jeroen Bruggeman (https://sites.google.com/site/jebrug/jeroen-bruggeman-social-science) and Gabor Csardi csardi.gabor@gmail.com

### References

Burt, R.S. (2004). Structural holes and good ideas. American Journal of Sociology 110, 349-399.

### Examples

 ```1 2``` ```g <- sample_gnp(20, 5/20) constraint(g) ```

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