Differences

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--- centrality [2015/11/24 09:29] – hkimscil
+++ centrality [2018/06/07 10:05] – hkimscil
@@ Line 4: / Line 4: @@
 ===== Closeness =====
+<code>setwd("D:/Users/Hyo/Cs-Kant/CS/Classes/sna_examples/sna_in_r")</code>
 <code># Social Network Analysis: Closeness Centrality
 library(sna)
@@ Line 19: / Line 20: @@
 </code>
-<code>gplot(L, displaylabels = T, vertex.cex = 1, label.cex = 2, edge.col="red",
+<code>gplot(L, displaylabels = T, vertex.cex = 1, label.cex = 2, edge.col="blue",
-             boxed.labels = F, arrowhead.cex = 1, mode = "kamadakawai")
+boxed.labels = F, arrowhead.cex = 1, mode = "kamadakawai")
 </code>
 {{centrality_suzuki.png}}
@@ Line 93: / Line 94: @@
 </code>
-</code>betweenness(L)
+<code>betweenness(L)
 </code>
 <code>[1]  0  0  0 36 32 30 24 14  0
@@ Line 117: / Line 118: @@
 </code>
 <code>[1] 56  0  0  0  0  0  0  0  0
+</code>
+<code># Two stars network
+twostars <- matrix(0,13,13)
+edges <- matrix(c(1,2,1,3,1,4,1,5,1,6,
+,7,7,8,8,13,9,13,10,13,11,13,12,13),
+                  byrow=T,ncol=2)
+twostars[edges] <- 1
+twostars <- twostars + t(twostars) - twostars * t(twostars)
+gplot(twostars, displaylabels=T, vertex.cex=1, label.cex=1,
+      edge.col="red", boxed.labels=F, arrowhead.cex=1, mode="kamadakawai")
+betweenness(twostars)
+closeness(twostars)
+</code>
+{{two_star_network.png}}
+<code>>> betweenness(twostars)
+ [1] 76  0  0  0  0 70 72 70  0  0  0  0 76
+> round(closeness(twostars),2)
+ [1] 0.35 0.27 0.27 0.27 0.27 0.39 0.40 0.39 0.27 0.27 0.27 0.27 0.35
+</code>
+===== Eigenvector =====
+__Eigenvector Centrality__
+  * 중요한 노드에 연결된 노드가 중요하다는 관점
+<code>rownames(knoke.infor)
+</code>
+<code>> rownames(knoke.infor)
+ [1] "COUN" "COMM" "EDUC" "INDU" "MAYR" "WRO"  "NEWS" "UWAY" "WELF" "WEST"
+</code>
+<code>round(evcent(knoke.infor),2)
+</code>
+<code>> round(evcent(knoke.infor),2)
+ [1] 0.25 0.41 0.36 0.26 0.47 0.15 0.22 0.35 0.21 0.33
+</code>
+<code>round(evcent(t(knoke.infor)),2)
+</code>
+<code>> round(evcent(t(knoke.infor)),2)
+ [1] 0.30 0.45 0.21 0.34 0.45 0.04 0.46 0.18 0.28 0.13
 </code>