Next to:Network7A12

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Source,Target,Cluster,WCD U.S,U.S,2,278 China,China,2,168 South Korea,South Korea,2,82 Canada,Canada,4,59 Taiwan,Taiwan,6,51 Germany,Germany,8,42 U.K,U.K,8,38 Australia,Australia,8,31 Spain,Spain,7,24.00106 Netherlands,Netherlands,9,21 Japan,Japan,10,19 France,France,12,18 Switzerland,Switzerland,13,14 Sweden,Sweden,14,12 Finland,Finland,1,9 Italy,Italy,13,9 Australia,U.K,8,5 Singapore,Singapore,3,5 Belgium,Belgium,7,4 Hong Kong,Hong Kong,5,4 China,U.S,2,3 Australia,China,8,3 Australia,Hong Kong,8,2 India,India,3,2 China,Hong Kong,2,2 South Korea,U.S,2,2 India,Singapore,3,2 China,New Zealand,2,1 Italy,Switzerland,13,1 Italy,Japan,13,1 India,U.S,3,1 China,U.K,2,1 Taiwan,U.S,6,1 New Zealand,New Zealand,11,1 Canada,U.S,4,1 China,Taiwan,2,1 Belgium,Spain,7,1 Germany,U.K,8,1

for Network7A12

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library(igraph) data <- data.frame(Source=c("U.S","China","South Korea","Canada","Taiwan","Germany","U.K","Australia","Spain","Netherlands","Japan","France","Switzerland","Sweden","Finland","Italy","Australia","Singapore","Belgium","Hong Kong","China","Australia","Australia","India","China","South Korea","India","China","Italy","Italy","India","China","Taiwan","New Zealand","Canada","China","Belgium","Germany") ,Target=c("U.S","China","South Korea","Canada","Taiwan","Germany","U.K","Australia","Spain","Netherlands","Japan","France","Switzerland","Sweden","Finland","Italy","U.K","Singapore","Belgium","Hong Kong","U.S","China","Hong Kong","India","Hong Kong","U.S","Singapore","New Zealand","Switzerland","Japan","U.S","U.K","U.S","New Zealand","U.S","Taiwan","Spain","U.K") ,Cluster=c(2,2,2,4,6,8,8,8,7,9,10,12,13,14,1,13,8,3,7,5,2,8,8,3,2,2,3,2,13,13,3,2,6,11,4,2,7,8) ,WCD=c(278,168,82,59,51,42,38,31,24.00106,21,19,18,14,12,9,9,5,5,4,4,3,3,2,2,2,2,2,1,1,1,1,1,1,1,1,1,1,1) ) #WCD=c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1) nodes <- data.frame(name=c("Germany","U.K","Belgium","Spain","China","Taiwan","Canada","U.S","New Zealand","India","Italy","Japan","Switzerland","Singapore","South Korea","Hong Kong","Australia","Finland","Sweden","France","Netherlands"), carac=c("8","8","7","7","2","2","4","4","11","3","13","13","13","3","2","2","8","1","14","12","9")) # data<-as.matrix.data.frame(data) # df.g <- graph.data.frame(d = data[,1:2], directed = FALSE) # plot(df.g, vertex.label = V(df.g)$name,vertex.color = "green") # Turn it into igraph object network <- graph_from_data_frame(d=data, vertices=nodes, directed=F) # Make a palette of 9 colors library(RColorBrewer) coul <- brewer.pal(9, "Set1") # Create a vector of color my_color <- coul[as.numeric(as.factor(V(network)$carac))] deg <- degree(network, mode="all") V(network)$size <- deg*3 # We could also use the audience size value: #V(network)$size <- V(network)$audience.size*0.6 # Make the plot # plot(network, vertex.color=my_color) # Add a legend #legend("bottomleft", legend=levels(as.factor(V(network)$carac)) , col = coul , bty = #"n", pch=20 , pt.cex = 3, cex = 1.5, text.col=coul , horiz = FALSE, inset = c(0.1, 0.1)) #plot(network, vertex.color=my_color, edge.width=E(network)$WCD*2 ) legend("bottomleft", legend=levels(as.factor(V(network)$carac)) , col = coul , bty = "n", pch=20 , pt.cex = 3, cex = 1.5, text.col=coul , horiz = FALSE, inset = c(0.1, 0.1)) plot(network, vertex.color=my_color, edge.width=E(network)$WCD*1/20,vertex.label.dist=1) #Adjust : E(network)$value*1/20 and V(network)$size <- deg*3 for edge and bubble sizes #legend(x=-1.1, y=-1.1, c("Newspaper","Television", "Online News"), pch=21, #col="#777777", pt.bg=my_color, pt.cex=2.5, bty="n", ncol=1) #https://oak.ucc.nau.edu//yc424/_book/data-to-network.html #plot(network, vertex.shape="none", vertex.label=V(net)$media, # vertex.label.font=2, vertex.label.color="gray40", # vertex.label.cex=.7, edge.color="gray85") #edge.start <- ends(network, es=E(network), names=F)[,1] #edge.col <- V(network)$color[edge.start] #plot(network, edge.color=edge.col, edge.curved=.1) #ceb<-cluster_edge_betweenness(network) #dendPlot(ceb,mode="hclust") #plot(ceb, network)