community

node_kernighanlin

Community graph partitioning algorithms

A set of tools for analysing multimodal networks.
All functions operate with matrices, edge lists,
and 'igraph', 'network', and 'tidygraph' objects,
and on one-mode, two-mode (bipartite), and sometimes three-mode networks.
It includes functions for measuring
centrality, centralization, cohesion, closure, and constraint,
as well as for network block-modelling and regression.
The package is released as a complement to
'Multimodal Political Networks' (2021, ISBN:9781108985000),
and includes various datasets used in the book in addition to other network data.

James Hollway

migraph

Tools for Multimodal Network Analysis

Jael Tan

Bernhard Bieri

Henrique Sposito

community function

<dl><dt>object</dt>
<dd>An object of a migraph-consistent class:<ul>
<li>matrix (adjacency or incidence) from <code>{base}</code> R</li>
<li>edgelist, a data frame from <code>{base}</code> R or tibble from <code>{tibble}</code></li>
<li>igraph, from the <code>{igraph}</code> package</li>
<li>network, from the <code>{network}</code> package</li>
<li>tbl_graph, from the <code>{tidygraph}</code> package</li>
</ul></dd></dl>

Arguments

<ul>
<li><code>node_kernighanlin()</code>: A greedy, iterative, deterministic graph
partitioning algorithm that results in a graph with two
equally-sized communities</li>
</ul>

Functions

Community graph partitioning algorithms — community

<dl>

<dt>object</dt>
<dd>An object of a migraph-consistent class:<ul>
<li>matrix (adjacency or incidence) from <code>{base}</code> R</li>
<li>edgelist, a data frame from <code>{base}</code> R or tibble from <code>{tibble}</code></li>
<li>igraph, from the <code>{igraph}</code> package</li>
<li>network, from the <code>{network}</code> package</li>
<li>tbl_graph, from the <code>{tidygraph}</code> package</li>
</ul></dd>

</dl>

community: Community graph partitioning algorithms

Description

Usage

Arguments

Functions

References

See Also

Examples