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network_position

Metrics using the community's graph object (representation of contributor network).

By level of observation:

contributors

  • [contributor_degree][pici.metrics.network.contributor_degree]
  • [contributor_centralities][pici.metrics.network.contributor_centralities]
  • [contributor_communities][pici.metrics.network.contributor_communities]

co_contributor_centralities(community)

Contributor centralities.

Includes degree centrality, betweenness centrality, and eigenvector centrality. Using networkx implementation.

Parameters:

Name Type Description Default
community pici.Community required

co_contributor_communities(community, leiden_lib='cdlib')

Find communities within the contributor network.

Uses weighted Leiden algorithm (Traag et al., 2018) implemented in cdlib.algorithms.leiden or leidgenalg.

Traag, Vincent, Ludo Waltman, and Nees Jan van Eck. From Louvain to Leiden: guaranteeing well-connected communities. arXiv preprint arXiv:1810.08473 (2018).

Parameters:

Name Type Description Default
leiden_lib

Which Leiden alg. implementation to use, 'cdlib' or

'cdlib'
community required

Returns:

Name Type Description
node_communities_map dict of node:list(communities)

List of

communities a contributor belongs to. See [

cdlib.NodeClustering.to_node_community_map]

(https://cdlib.readthedocs.io/en/latest/reference/classes

/node_clustering.html).

co_contributor_degree(community)

Number of contributors each contributor has co-authored with in a thread.

Using implementation of networkx.Graph.degree.

TODO

document

Parameters:

Name Type Description Default
community pici.Community required

initiator_centrality_in_co_contributor_network(community, k=None)

TODO: implement using _initial_post_author_network_metric()

Parameters:

Name Type Description Default
community required
k None