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--- r:social_network_analysis [2023/06/12 08:12] – [stu x class 처럼 분석한 예] hkimscil
+++ r:social_network_analysis [2023/11/22 22:02] (current) – [Hawthorne study] hkimscil
@@ Line 27: / Line 27: @@
 <code>
+V(g)$type <- bipartite_mapping(g)$type
 types <- V(g)$type
 deg <- degree(g)
@@ Line 183: / Line 184: @@
 actor_matrix <- bipartite_matrix %*% t(bipartite_matrix)
 event_matrix <- t(bipartite_matrix) %*% bipartite_matrix
 diag(actor_matrix) <- 0
@@ Line 194: / Line 196: @@
 actor_g_cff_2 <- graph_from_adjacency_matrix(actor_matrix_cff_2,
-                                       mode = "undirected",
+                                             mode = "undirected",
-                                       weighted = TRUE)
+                                             weighted = TRUE)
 actor_g_cff_3 <- graph_from_adjacency_matrix(actor_matrix_cff_3,
-                                       mode = "undirected",
+                                             mode = "undirected",
-                                       weighted = TRUE)
+                                             weighted = TRUE)
+V(actor_g)$size <- betweenness(actor_g)
+V(actor_g_cff_2)$size <- betweenness(actor_g_cff_2)
+V(actor_g_cff_3)$size <- betweenness(actor_g_cff_3)
+V(actor_g)$label.cex <- betweenness(actor_g) * 0.2
+V(actor_g_cff_2)$label.cex <- betweenness(actor_g_cff_2) * 0.1
+V(actor_g_cff_3)$label.cex <- betweenness(actor_g_cff_3) * 0.4
 actor_g
 actor_g_cff_2
@@ Line 228: / Line 238: @@
      vertex.label.family= fnts[as.numeric(V(g)$type)+1],
      edge.color="red", edge.width=3
-) </code>
+)
+</code>
-[{{:r:pasted:20230612-080626.png|actor_g}}] \\
+[{{:r:pasted:20230612-081851.png|actor_g}}] \\
-[{{:r:pasted:20230612-080636.png|actor_g_cff_2}}] \\
+[{{:r:pasted:20230612-082040.png|actor_g_cff_2}}] \\
-[{{:r:pasted:20230612-080646.png|actor_g_cff_3}}]
+[{{:r:pasted:20230612-082055.png|actor_g_cff_3}}]