Measures of network topological features

```
graph_core(object, membership = NULL)
graph_factions(object, membership = NULL)
graph_modularity(object, membership = NULL, resolution = 1)
graph_smallworld(object, times = 100)
graph_balance(object)
```

`{signnet}`

by David Schoch

- object
An object of a migraph-consistent class:

matrix (adjacency or incidence) from

`{base}`

Redgelist, a data frame from

`{base}`

R or tibble from`{tibble}`

igraph, from the

`{igraph}`

packagenetwork, from the

`{network}`

packagetbl_graph, from the

`{tidygraph}`

package

- membership
A vector of partition membership.

- resolution
A proportion indicating the resolution scale. By default 1.

- times
Integer of number of simulations.

`graph_core`

: Returns correlation between a given network and a core-periphery model with the same dimensions.`graph_factions`

: Returns correlation between a given network and a component model with the same dimensions.`graph_modularity`

: Returns modularity of one- or two-mode networks based on nodes' membership in pre-defined clusters.`graph_smallworld`

: Returns small-world metrics for one- and two-mode networks. Small-world networks can be highly clustered and yet have short path lengths.`graph_balance`

: Returns the structural balance index on the proportion of balanced triangles, ranging between`0`

if all triangles are imbalanced and`1`

if all triangles are balanced.

Borgatti, Stephen P., and Martin G. Everett. 2000.
“Models of Core/Periphery Structures.”
*Social Networks* 21(4):375–95.
https://doi.org/10.1016/S0378-8733(99)00019-2

Murata, Tsuyoshi. 2010. Modularity for Bipartite Networks.
In: Memon, N., Xu, J., Hicks, D., Chen, H. (eds)
*Data Mining for Social Network Data. Annals of Information Systems*, V1ol 12.
Springer, Boston, MA.
doi:10.1007/978-1-4419-6287-4_7

Watts, Duncan J., and Steven H. Strogatz. 1998.
“Collective Dynamics of ‘Small-World’ Networks.”
*Nature* 393(6684):440–42.
doi:10.1038/30918
.

`graph_transitivity()`

and `graph_equivalency()`

for how clustering is calculated

Other measures:
`centralisation`

,
`centrality`

,
`closure`

,
`cohesion()`

,
`diversity`

,
`holes`

```
graph_core(ison_adolescents)
#> [1] 0.164
graph_core(ison_southern_women)
#> [1] -0.299
graph_factions(ison_adolescents)
#> [1] 0.174
graph_factions(ison_southern_women)
#> [1] 0.485
graph_modularity(ison_adolescents,
node_kernighanlin(ison_adolescents))
#> [1] -0.205
graph_modularity(ison_southern_women,
node_kernighanlin(ison_southern_women))
#> [1] -0.458
graph_smallworld(ison_brandes)
#> [1] 0
graph_smallworld(ison_southern_women)
#> [1] 1.32
graph_balance(ison_marvel_relationships)
#> [1] 0.668
```