Description Usage Arguments Details Value Author(s) References See Also Examples

This function tries to find dense subgraph, also called communities in graphs via directly optimizing a modularity score.

1 2 3 4 5 6 7 | ```
cluster_fast_greedy(
graph,
merges = TRUE,
modularity = TRUE,
membership = TRUE,
weights = E(graph)$weight
)
``` |

`graph` |
The input graph |

`merges` |
Logical scalar, whether to return the merge matrix. |

`modularity` |
Logical scalar, whether to return a vector containing the modularity after each merge. |

`membership` |
Logical scalar, whether to calculate the membership vector corresponding to the maximum modularity score, considering all possible community structures along the merges. |

`weights` |
If not |

This function implements the fast greedy modularity optimization algorithm for finding community structure, see A Clauset, MEJ Newman, C Moore: Finding community structure in very large networks, http://www.arxiv.org/abs/cond-mat/0408187 for the details.

`cluster_fast_greedy`

returns a `communities`

object, please see the `communities`

manual page for details.

Tamas Nepusz ntamas@gmail.com and Gabor Csardi csardi.gabor@gmail.com for the R interface.

A Clauset, MEJ Newman, C Moore: Finding community structure in very large networks, http://www.arxiv.org/abs/cond-mat/0408187

`communities`

for extracting the results.

See also `cluster_walktrap`

,
`cluster_spinglass`

,
`cluster_leading_eigen`

and
`cluster_edge_betweenness`

for other methods.

1 2 3 4 5 | ```
g <- make_full_graph(5) %du% make_full_graph(5) %du% make_full_graph(5)
g <- add_edges(g, c(1,6, 1,11, 6, 11))
fc <- cluster_fast_greedy(g)
membership(fc)
sizes(fc)
``` |

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