get_adaptive_rank: Returns ranks from 1 to highest rank before the graph is...

In seekme94/influence.mining: Provides various methods for influence mining on Graphs

Returns ranks from 1 to highest rank before the graph is discontinued, using scores of nodes (e.g. Degree, Pagerank, Coreness, etc.)

Description

Returns ranks from 1 to highest rank before the graph is discontinued, using scores of nodes (e.g. Degree, Pagerank, Coreness, etc.)

Usage

get_adaptive_rank(
  graph,
  ranking_method = c("CORENESS", "PAGERANK", "COLLECTIVE_INFLUENCE", "DEGREE",
    "ECCENTRICITY", "AVERAGE_DISTANCE", "BARYCENTER", "BETWEENNESS", "BOTTLENECK",
    "CENTROID", "CLOSENESS", "CLUSTERRANK", "COMMUNITY_BETWEENNESS",
    "COMMUNITY_CENTRALITY", "CROSS_CLIQUE", "CURRENTFLOW_CLOSENESS", "DECAY",
    "EDGE_PERCOLATION", "EIGENVECTOR", "ENTROPY", "FREEMAN_CLOSENESS", "GEODESIC_K_PATH",
    "HUBBELL", "KATZ", "LAPLACIAN", "LATORA_CLOSENESS", "LEADERRANK", "LEVERAGE",
    "LINCENT", "LOBBY", "MARKOV", "MAX_NEIGHBORHOOD_COMPONENT",     
    "MAX_NEIGHBORHOOD_DENSITY", "PAIRWISE_DISCONNECTIVITY", "RADIALITY",
    "RESIDUAL_CLOSENESS", "SALSA", "SEMILOCAL", "TOPOLOGICAL_COEFFICIENT",
    "VITALITY_CLOSENESS"),
  mode = "all"
)

Arguments

graph	the igraph object
ranking_method	the adaptive method to use. Value must be "DEGREE", "BETWEENNESS", "CLOSENESS", "EIGENVECTOR", "ECCENTRICITY", "CORENESS", "PAGERANK", "COLLECTIVE_INFLUENCE"

Value

vector of ranks

seekme94/influence.mining documentation built on Aug. 2, 2022, 10:19 p.m.