R/ITNproperties_function.R

In MatthewSmith430/ITNr: Analysis of the International Trade Network

#' @title ITN Properties
#'
#' @description This function calculates network level properties for the ITN. These include:
#' -Size (number of nodes) -Density -Reciprocity -Diameter
#' -Average path length -Average node strength -Average Degree
#' -Betweenness Centralisation -Closeness Centralisation -Eigenvector Centralisation
#' -Out Degree Centralisation -In Degree Centralisation -All Degree Centralisation -Clustering coefficent (transitivity)
#' -Clustering Weighted -Region Homophily -Degree Assortativity
#' @param gs International Trade Network - igraph object
#' @param weighted TRUE-weighted, FALSE-binary
#' @export
#' @return Table of centrality results (dataframe)
#' @examples
#' ##Load the network
#' data(ELEnet16)
#'
#' ##Calculate the network properties
#' ITNPROP<-ITNproperties(ELEnet16,TRUE)
#'
ITNproperties<-function(gs,weighted){
  if (weighted==TRUE){
    net <- cbind(igraph::get.edgelist(gs, names=FALSE), igraph::E(gs)$weight)
    net <- tnet::as.tnet(net, type="weighted one-mode tnet")

    WeightDegAll<-tnet::degree_w(net,measure=c("degree","output"), type="all")
    WeightedClustering<-tnet::clustering_w(net)

    Wall<-WeightDegAll[,3]
    Dall<-WeightDegAll[,2]

    BetCen<-igraph::centr_betw(gs)
    closenesscen<-igraph::centr_clo(gs,mode="total")
    DegOutCen<-igraph::centr_degree(gs,mode="out")
    DegInCen<-igraph::centr_degree(gs,mode="in")
    DegAllCen<-igraph::centr_degree(gs,mode="all")
    EigCen<-igraph::centr_eigen(gs)

    AveragePathLength<-igraph::mean_distance(gs, directed=TRUE)

    AverageNodeStrengthAll<-mean(Wall)
    AverageDegreeAll<-mean(Dall)

    den<-igraph::graph.density(gs,loops=F)
    DIA<-igraph::diameter(gs, directed = T)
    size<-igraph::vcount(gs)
    RECIP<-igraph::reciprocity(gs)

    CC<-igraph::transitivity(gs,"global")

    RegionHomophily<-igraph::assortativity_nominal(gs, igraph::V(gs)$region, directed=T)
    DegAssort<-igraph::assortativity_degree(gs, directed=T)

    myDF<-data.frame(
      Size=size,
      Density=den,
      Reciprocity=RECIP,
      Diameter=DIA,
      Average.path.lenth=AveragePathLength,
      Average.node.stregnth=AverageNodeStrengthAll,
      Average.Degree=AverageDegreeAll,
      Betweenness.Centralisation=BetCen$centralization,
      Closeness.Centralisation=closenesscen$centralization,
      Eigenvector.Centralisation=EigCen$centralization,
      Out.Degree.Centralisation=DegOutCen$centralization,
      In.Degree.Centralisation=DegInCen$centralization,
      All.Degree.Centralisation=DegAllCen$centralization,
      clustering.coefficient.transitivity=CC,
      Clustering.Weighted=WeightedClustering,
      Region.Homophily=RegionHomophily,
      Degree.Assortativity=DegAssort
    )
    myDF<-round_df(myDF,4)
    myDF<-t(myDF)
    myDF<-as.data.frame(myDF)
    rownames(myDF)<-c(
      "Size",
      "Density",
      "Reciprocity",
      "Diameter",
      "Average.path.length",
      "Average.node.strength",
      "Average.Degree",
      "Betweenness.Centralisation",
      "Closeness.Centralisation",
      "Eigenvector.Centralisation",
      "Out.Degree.Centralisation",
      "In.Degree.Centralisation",
      "All.Degree.Centralisation",
      "Clustering.coefficient.transitivity",
      "Clustering.Weighted",
      "Region.Homophily",
      "Degree.Assortativity")
    colnames(myDF)<-"Network.Properties"


  }else{
    BetCen<-igraph::centr_betw(gs)
    closenesscen<-igraph::centr_clo(gs,mode="total")
    DegOutCen<-igraph::centr_degree(gs,mode="out")
    DegInCen<-igraph::centr_degree(gs,mode="in")
    DegAllCen<-igraph::centr_degree(gs,mode="all")
    EigCen<-igraph::centr_eigen(gs)

    AveragePathLength<-igraph::mean_distance(gs, directed=TRUE)


    AverageDegreeAll<-mean(igraph::degree(gs,mode="all"))

    den<-igraph::graph.density(gs,loops=F)
    DIA<-igraph::diameter(gs, directed = T)
    size<-igraph::vcount(gs)
    RECIP<-igraph::reciprocity(gs)

    CC<-igraph::transitivity(gs,"global")

    RegionHomophily<-igraph::assortativity_nominal(gs, igraph::V(gs)$region, directed=T)
    DegAssort<-igraph::assortativity_degree(gs, directed=T)

    myDF<-data.frame(
      Size=size,
      Density=den,
      Reciprocity=RECIP,
      Diameter=DIA,
      Average.path.lenth=AveragePathLength,
      Average.Degree=AverageDegreeAll,
      Betweenness.Centralisation=BetCen$centralization,
      Closeness.Centralisation=closenesscen$centralization,
      Eigenvector.Centralisation=EigCen$centralization,
      Out.Degree.Centralisation=DegOutCen$centralization,
      In.Degree.Centralisation=DegInCen$centralization,
      All.Degree.Centralisation=DegAllCen$centralization,
      clustering.coefficient.transitivity=CC,
      Region.Homophily=RegionHomophily,
      Degree.Assortativity=DegAssort
    )
    myDF<-round_df(myDF,4)
    myDF<-t(myDF)
    myDF<-as.data.frame(myDF)
    rownames(myDF)<-c(
      "Size",
      "Density",
      "Reciprocity",
      "Diameter",
      "Average.path.length",
      "Average.Degree",
      "Betweenness.Centralisation",
      "Closeness.Centralisation",
      "Eigenvector.Centralisation",
      "Out.Degree.Centralisation",
      "In.Degree.Centralisation",
      "All.Degree.Centralisation",
      "Clustering.coefficient.transitivity",
      "Region.Homophily",
      "Degree.Assortativity")
    colnames(myDF)<-"Network.Properties"

  }
  return(myDF)
}