This function computes multitude centrality measures of an igraph object.

calculate_centralities(x, except = NULL, include = NULL, weights = NULL)

Arguments

x

the component of a network as an igraph object

except

A vector containing names of centrality measures which could be omitted from the calculations.

include

A vector including names of centrality measures which should be computed.

weights

A character scalar specifying the edge attribute to use.(default=NULL)

Value

A list concluding centrality measure values in which the columns indicate centralities and the rows show the vertices.

Details

This function calculates various types of centrality measures which are applicable to the network topology and returns the results as a list. In "except" argument, you can specify centrality measures which is not necessary to calculate.

References

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See also

Examples

data("zachary") p <- proper_centralities(zachary)
#> [1] "subgraph centrality scores" #> [2] "Topological Coefficient" #> [3] "Average Distance" #> [4] "Barycenter Centrality" #> [5] "BottleNeck Centrality" #> [6] "Centroid value" #> [7] "Closeness Centrality (Freeman)" #> [8] "ClusterRank" #> [9] "Decay Centrality" #> [10] "Degree Centrality" #> [11] "Diffusion Degree" #> [12] "DMNC - Density of Maximum Neighborhood Component" #> [13] "Eccentricity Centrality" #> [14] "Harary Centrality" #> [15] "eigenvector centralities" #> [16] "K-core Decomposition" #> [17] "Geodesic K-Path Centrality" #> [18] "Katz Centrality (Katz Status Index)" #> [19] "Kleinberg's authority centrality scores" #> [20] "Kleinberg's hub centrality scores" #> [21] "clustering coefficient" #> [22] "Lin Centrality" #> [23] "Lobby Index (Centrality)" #> [24] "Markov Centrality" #> [25] "Radiality Centrality" #> [26] "Shortest-Paths Betweenness Centrality" #> [27] "Current-Flow Closeness Centrality" #> [28] "Closeness centrality (Latora)" #> [29] "Communicability Betweenness Centrality" #> [30] "Community Centrality" #> [31] "Cross-Clique Connectivity" #> [32] "Entropy Centrality" #> [33] "EPC - Edge Percolated Component" #> [34] "Laplacian Centrality" #> [35] "Leverage Centrality" #> [36] "MNC - Maximum Neighborhood Component" #> [37] "Hubbell Index" #> [38] "Semi Local Centrality" #> [39] "Closeness Vitality" #> [40] "Residual Closeness Centrality" #> [41] "Stress Centrality" #> [42] "Load Centrality" #> [43] "Flow Betweenness Centrality" #> [44] "Information Centrality" #> [45] "Dangalchev Closeness Centrality" #> [46] "Group Centrality" #> [47] "Harmonic Centrality" #> [48] "Local Bridging Centrality" #> [49] "Wiener Index Centrality"
calculate_centralities(zachary, include = "Degree Centrality")
#> $`Degree Centrality` #> [1] 16 9 10 6 3 4 4 4 5 2 3 1 2 5 2 2 2 2 2 3 2 2 2 5 3 #> [26] 3 2 4 3 4 4 6 12 17 #>