network_summary {wpa}

Summarise node centrality statistics with an igraph object

Description

Pass an igraph object to the function and obtain centrality statistics for each node in the object as a data frame. This function works as a wrapper of the centralization functions in 'igraph'.

Usage

network_summary(graph, hrvar = NULL, return = "table")

Arguments

graph

'igraph' object that can be returned from network_g2g() or network_p2p()when the return argument is set to "network".

hrvar

String containing the name of the HR Variable by which to split metrics. Defaults to NULL.

return

String specifying what output to return. Valid inputs include:

• "table"

• "network"

• "plot"

See Value for more information.

Value

By default, a data frame containing centrality statistics. Available statistics include:

• betweenness: number of shortest paths going through a node.

• closeness: number of steps required to access every other node from a given node.

• degree: number of connections linked to a node.

• eigenvector: a measure of the influence a node has on a network.

• pagerank: calculates the PageRank for the specified vertices. Please refer to the igraph package documentation for the detailed technical definition.

When "network" is passed to "return", an 'igraph' object is returned with additional node attributes containing centrality scores.

When "plot" is passed to "return", a summary table is returned showing the average centrality scores by HR attribute. This is currently available if there is a valid HR attribute.

See Also

Other Network: external_network_plot(), g2g_data, internal_network_plot(), network_describe(), network_g2g(), network_p2p(), p2p_data_sim()

Examples

# Simulate a p2p network
p2p_data <- p2p_data_sim(size = 100)
g <- network_p2p(data = p2p_data, return = "network")

# Return summary table
network_summary(graph = g, return = "table")

# Return network with node centrality statistics
network_summary(graph = g, return = "network")

# Return summary plot
network_summary(graph = g, return = "plot", hrvar = "Organization")

# Simulate a g2g network and return table
g2 <- g2g_data %>% network_g2g(return = "network")
network_summary(graph = g2, return = "table")