group_centrality

# Set up the network objects
friendship.aj <- matrix(c(NA, 0, 1, 1, 1,
                          0, NA, 0, 0, 0,
                          1, 0, NA, 0, 1,
                          1, 1, 0, NA, 1,
                          1, 0, 0, 0, NA),
                        nrow = 5, byrow = TRUE)
friendship.net.dir <- network(friendship.aj)
friendship.net.undir <- network(friendship.aj, directed = FALSE)

# Here's the function
group_centrality <- function(net) {
    # Return a single centrality score for a whole network
    if(!is.network(net))
    {
        stop("Object must be a network")
    }
    d_star <- (max(degree(net, cmode = 'outdegree')))
    print(d_star)
    for(i in 1:network.size(net))
    {
        if(is.directed(net))
        {
            print("Network is directed")
            numerator <- d_star - degree(net, cmode = 'outdegree')[i]
            print(numerator)
            denominator <- (((network.size(net) - 1)^2))
            print(denominator)
            centrality <- sum((d_star - degree(net, cmode = 'outdegree')[i])/
                (((network.size(net) - 1)^2)))
        } else {
            print("Network is undirected")
            numerator <- d_star - degree(net, cmode = 'outdegree')[i]
            print(numerator)
            denominator <- (((network.size(net)) - 1)*(network.size(net) - 2))
            print(denominator)
            centrality <- sum((d_star - degree(net, cmode = 'outdegree')[i])/
                (((network.size(net)) - 1)*(network.size(net) - 2)))
        }

    }
    return(centrality)
}