# transitivity

From igraph v0.5.3
by Gabor Csardi

##### Transitivity of a graph

Transitivity measures the probability that the adjacent vertices of a vertex are connected. This is sometimes also called the clustering coefficient.

- Keywords
- graphs

##### Usage

```
transitivity(graph, type=c("undirected", "global", "globalundirected",
"localundirected", "local", "average", "localaverage",
"localaverageundirected"), vids=NULL)
```

##### Arguments

- graph
- The graph to analyze.
- type
- The type of the transitivity to calculate. Possible
values:
`global`

##### Value

- For
a single number, or`global`

`NaN`

if there are no connected triples in the graph.For

a vector of transitivity scores, one for each vertex in`local`

.`vids`

##### concept

- Transitivity
- Clustering coefficient

##### item

vids

##### code

`V(graph)`

##### References

Wasserman, S., and Faust, K. (1994). *Social Network
Analysis: Methods and Applications.* Cambridge: Cambridge University
Press.

##### Examples

```
g <- graph.ring(10)
transitivity(g)
g2 <- erdos.renyi.game(1000, 10/1000)
transitivity(g2) # this is about 10/1000
```

*Documentation reproduced from package igraph, version 0.5.3, License: GPL (>= 2)*

### Community examples

Looks like there are no examples yet.