EduStructure

Структура отношений на проекте edu

Старая версия

lt2 <- data.frame(User = paste("A",hist[,1],sep=":" ) , Page = paste("O",hist[,2],sep=":"), Action = hist[,3] )  # Agent vs Object
lt2.network <- graph.data.frame(lt2,directed=T) ;
E(lt2.network)$color <- ifelse(E(lt2.network)$Action =='createidea', "red", "green")

lt2.network <- simplify(lt2.network)
V(lt2.network)$color <-ifelse (substring(V(lt2.network)$name, 1, 1) == "A",'red','blue')
V(lt2.network)$shape <-ifelse (substring(V(lt2.network)$name, 1, 1) == "A",'circle','square')
set.seed(42)
plot(lt2.network, edge.arrow.size=.2,vertex.label=NA, vertex.size=4, layout=layout.fruchterman.reingold)  # Test
plot(lt2.network, edge.arrow.size=.2,vertex.label=NA, vertex.size=1, layout=layout.kamada.kawai)  # Test
l <- delete.vertices(lt2.network,V(lt2.network)[degree(lt2.network)<=1])
plot(l, edge.arrow.size=.2,vertex.label=NA, vertex.size=1, layout=layout.kamada.kawai)  # Test
plot(l, edge.arrow.size=.2,vertex.label=NA, vertex.size=3, layout=layout.fruchterman.reingold)# Test

plot(l, edge.arrow.size=.2,vertex.label=NA, vertex.size=2, layout=layout.kamada.kawai)

1. Test

deg <- degree(lt2.network, mode="all")

1. V(lt2.network)$label <-ifelse (substring(V(lt2.network)$name, 1, 1) == "U" & deg > 50, V(lt2.network)$name, NA)

plot(lt2.network, edge.arrow.size=.4,vertex.size=deg/10, layout=layout.kamada.kawai)

1. 1. From bigraph to monograph

g2 <- lt2 ; A <- spMatrix(nrow=length(unique(g2$User)),

             ncol=length(unique(g2$Page)),
             i = as.numeric(factor(g2$User)),
             j = as.numeric(factor(g2$Page)),
             x = rep(1, length(as.numeric(g2$User))) )

row.names(A) <- levels(factor(g2$User)) colnames(A) <- levels(factor(g2$Page)) Arow <- A %*% t(A) ## Persons Acol <- t(A) %*% A ## Groups - Objects gm <- graph_from_adjacency_matrix(Arow, weighted=T, mode = "undirected") gm <- graph_from_adjacency_matrix(Acol, weighted=T, mode = "undirected") gm <- simplify(gm) E(gm)$label = NA V(gm)$label = NA set.seed(10)

1. deg <- degree(gm, mode="all")

plot(gm, edge.arrow.size=.4, vertex.size=5, edge.width = 1, vertex.color="red", layout=layout.fruchterman.reingold) plot(gm, edge.arrow.size=.4, vertex.size=5, vertex.shape='square', vertex.color="blue", edge.width = 1, layout=layout.fruchterman.reingold)

1. 1. 1. Metrics

gm graph.density(gm) # Density (No of edges / possible edges) clusters(gm)$no ## # Число островов - не связанных между собой компонентов diameter(gm) ## Diameter of the graph measure the longest distance between any two nodes

1. clusters(gm, mode="weak") # Connected Component

transitivity(gm, type="global") # Global cluster coefficient centralization.betweenness (gm, directed = FALSE, nobigint = TRUE, normalized = TRUE) largest.cliques(gm)

Связи между проектами

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