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r:social_network_analysis_tutorial

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r:social_network_analysis_tutorial [2019/11/27 08:13] – [Using ifelse] hkimscilr:social_network_analysis_tutorial [2023/11/23 08:50] (current) – hkimscil
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 ====== T1. ====== ====== T1. ======
 +''%%install.packages("igraph")%%''
 +see [[https://igraph.org/r/doc/index.html]]
 ===== Dataset ===== ===== Dataset =====
 <file csv star-wars-network-edges.csv> <file csv star-wars-network-edges.csv>
Line 657: Line 659:
 </code> </code>
  
 +<code>
 +par(mar=c(0,0,0,0))
 +plot(g)
 +</code>
 +{{:r:pasted:20191127-074438.png}}
 +
 +===== %in% =====
 +
 +<code>
 +# what does %in% do?
 +1 %in% c(1,2,3,4)
 +1 %in% c(2,3,4)
 +</code>
 +
 +<code>
 +> 1 %in% c(1,2,3,4)
 +[1] TRUE
 +> 1 %in% c(2,3,4)
 +[1] FALSE
 +> 
 +</code>
 +
 +<code>
 +dark_side <- c("DARTH VADER", "MOTTI", "TARKIN")
 +light_side <- c("R2-D2", "CHEWBACCA", "C-3PO", "LUKE", "CAMIE", "BIGGS",
 +                "LEIA", "BERU", "OWEN", "OBI-WAN", "HAN", "DODONNA",
 +                "GOLD LEADER", "WEDGE", "RED LEADER", "RED TEN", "GOLD FIVE")
 +other <- c("GREEDO", "JABBA")
 +# node we'll create a new color variable as a node property
 +V(g)$color <- NA # V(g)에 color라는 컬럼을 만든다
 +V(g)$color[V(g)$name %in% dark_side] <- "red" 
 +# V(g)$name이 dark_side에 있는 이름이면 color 컬럼에 "red"를 적는다.
 +V(g)$color[V(g)$name %in% light_side] <- "gold"
 +V(g)$color[V(g)$name %in% other] <- "grey20"
 +vertex_attr(g)
 +</code>
 +
 +<code>
 +par(mar=c(0,0,0,0))
 +plot(g)
 +legend(x=.75, y=.75, legend=c("Dark side", "Light side", "Other"), 
 +       pch=21, pt.bg=c("red", "gold", "grey20"), pt.cex=2, bty="n")
 +</code>
 +{{:r:pasted:20191127-075029.png}}
 +
 +===== Edges =====
 +<code>
 +E(g)$width <- log(E(g)$weight) + 1.5 # create width column in the graph, g
 +edge_attr(g)
 +</code>
 +<code>
 +> E(g)$width <- log(E(g)$weight) + 1.5 # create width column in the graph, g
 +> edge_attr(g)
 +$weight
 + [1] 17 13  6  5  5  3  1  7  5 16 19 11  1  1  2  2
 +[17]  4  1  3  3  2  3 18  2  6 17  1 19  6  1  2  1
 +[33]  7  9 26  1  1  6  1  1 13  1  1  1  1  1  1  2
 +[49]  1  1  3  3  1  1  3  1  2  1  1  1
 +
 +$width
 + [1] 4.333213 4.064949 3.291759 3.109438 3.109438
 + [6] 2.598612 1.500000 3.445910 3.109438 4.272589
 +[11] 4.444439 3.897895 1.500000 1.500000 2.193147
 +[16] 2.193147 2.886294 1.500000 2.598612 2.598612
 +[21] 2.193147 2.598612 4.390372 2.193147 3.291759
 +[26] 4.333213 1.500000 4.444439 3.291759 1.500000
 +[31] 2.193147 1.500000 3.445910 3.697225 4.758097
 +[36] 1.500000 1.500000 3.291759 1.500000 1.500000
 +[41] 4.064949 1.500000 1.500000 1.500000 1.500000
 +[46] 1.500000 1.500000 2.193147 1.500000 1.500000
 +[51] 2.598612 2.598612 1.500000 1.500000 2.598612
 +[56] 1.500000 2.193147 1.500000 1.500000 1.500000
 +</code>
 +
 +<code>
 +par(mar=c(0,0,0,0))
 +plot(g)
 +</code>
 +{{:r:pasted:20191127-080219.png}}
 +
 +<code>
 +par(mfrow=c(2, 3), mar=c(0,0,1,0))
 +plot(g, layout=layout_randomly, main="Random")
 +plot(g, layout=layout_in_circle, main="Circle")
 +plot(g, layout=layout_as_star, main="Star")
 +plot(g, layout=layout_as_tree, main="Tree")
 +plot(g, layout=layout_on_grid, main="Grid")
 +plot(g, layout=layout_with_fr, main="Force-directed")
 +par(mfrow=c(1, 1), mar=c(0,0,0,0)) # set it back to the previous setting
 +</code>
 +{{:r:pasted:20191127-080437.png}}
 +
 +cf. layout_with_fr: The Fruchterman-Reingold layout algorithm see [[https://www.rdocumentation.org/packages/igraph/versions/1.3.5/topics/layout_with_fr]] page
 +<code>
 +par(mfrow=c(1,2))
 +set.seed(777)
 +fr <- layout_with_fr(g, niter=1000)
 +par(mar=c(0,0,0,0)); plot(g, layout=fr)
 +set.seed(666)
 +fr <- layout_with_fr(g, niter=1000)
 +par(mar=c(0,0,0,0)); plot(g, layout=fr)
 +
 +</code>
 +{{:r:pasted:20191127-080758.png}}
 +
 +
 +===== Measurements =====
 +<code>
 +degree(g, mode = "all")
 +closeness(g, mode = "all", weights = NA, normalized = T)
 +betweenness(g, directed = F, weights = NA, normalized = T)
 +</code>
 +
 +<code>
 +> degree(g, mode = "all")
 +      R2-D2   CHEWBACCA       C-3PO        LUKE DARTH VADER       CAMIE       BIGGS 
 +          7           8          10          15           5           2           7 
 +       LEIA        BERU        OWEN     OBI-WAN       MOTTI      TARKIN         HAN 
 +         12           4           3           7           3           3           8 
 +     GREEDO       JABBA     DODONNA GOLD LEADER       WEDGE  RED LEADER     RED TEN 
 +          1           1           5           5           5           7           2 
 +  GOLD FIVE 
 +          0 
 +> closeness(g, mode = "all", weights = NA, normalized = T)
 +      R2-D2   CHEWBACCA       C-3PO        LUKE DARTH VADER       CAMIE       BIGGS 
 + 0.38181818  0.38888889  0.40384615  0.44680851  0.32812500  0.32307692  0.36842105 
 +       LEIA        BERU        OWEN     OBI-WAN       MOTTI      TARKIN         HAN 
 + 0.42000000  0.35000000  0.32812500  0.38181818  0.31343284  0.31343284  0.38888889 
 +     GREEDO       JABBA     DODONNA GOLD LEADER       WEDGE  RED LEADER     RED TEN 
 + 0.28767123  0.28767123  0.34426230  0.33870968  0.33870968  0.36842105  0.32307692 
 +  GOLD FIVE 
 + 0.04545455 
 +Warning message:
 +In closeness(g, mode = "all", weights = NA, normalized = T) :
 +  At centrality.c:2784 :closeness centrality is not well-defined for disconnected graphs
 +> betweenness(g, directed = F, weights = NA, normalized = T)
 +      R2-D2   CHEWBACCA       C-3PO        LUKE DARTH VADER       CAMIE       BIGGS 
 +0.011904762 0.035487528 0.057596372 0.297278912 0.011904762 0.000000000 0.032142857 
 +       LEIA        BERU        OWEN     OBI-WAN       MOTTI      TARKIN         HAN 
 +0.217120181 0.005442177 0.000000000 0.014852608 0.000000000 0.000000000 0.176190476 
 +     GREEDO       JABBA     DODONNA GOLD LEADER       WEDGE  RED LEADER     RED TEN 
 +0.000000000 0.000000000 0.011111111 0.003174603 0.003174603 0.032142857 0.000000000 
 +  GOLD FIVE 
 +0.000000000 
 +> 
 +</code>
 +
 +<code>
 +g.c.deg <- degree(g, mode = "all")
 +g.c.clo <- closeness(g, mode = "all", weights = NA, normalized = T)
 +g.c.bet <- betweenness(g, directed = F, weights = NA, normalized = T)
 +tmp <- data.frame(g.c.deg, g.c.clo, g.c.bet)
 +tmp[order(-g.c.clo, -g.c.bet),]
 +</code>
 +
 +<code>
 +> g.c.deg <- degree(g, mode = "all")
 +> g.c.clo <- closeness(g, mode = "all", weights = NA, normalized = T)
 +Warning message:
 +In closeness(g, mode = "all", weights = NA, normalized = T) :
 +  At centrality.c:2784 :closeness centrality is not well-defined for disconnected graphs
 +> g.c.bet <- betweenness(g, directed = F, weights = NA, normalized = T)
 +> tmp <- data.frame(g.c.deg, g.c.clo, g.c.bet)
 +> 
 +> tmp
 +            g.c.deg    g.c.clo     g.c.bet
 +R2-D2             7 0.38181818 0.011904762
 +CHEWBACCA         8 0.38888889 0.035487528
 +C-3PO            10 0.40384615 0.057596372
 +LUKE             15 0.44680851 0.297278912
 +DARTH VADER       5 0.32812500 0.011904762
 +CAMIE             2 0.32307692 0.000000000
 +BIGGS             7 0.36842105 0.032142857
 +LEIA             12 0.42000000 0.217120181
 +BERU              4 0.35000000 0.005442177
 +OWEN              3 0.32812500 0.000000000
 +OBI-WAN           7 0.38181818 0.014852608
 +MOTTI             3 0.31343284 0.000000000
 +TARKIN            3 0.31343284 0.000000000
 +HAN               8 0.38888889 0.176190476
 +GREEDO            1 0.28767123 0.000000000
 +JABBA             1 0.28767123 0.000000000
 +DODONNA           5 0.34426230 0.011111111
 +GOLD LEADER       5 0.33870968 0.003174603
 +WEDGE             5 0.33870968 0.003174603
 +RED LEADER        7 0.36842105 0.032142857
 +RED TEN           2 0.32307692 0.000000000
 +GOLD FIVE         0 0.04545455 0.000000000
 +> 
 +> tmp[order(-g.c.clo, -g.c.bet),]
 +            g.c.deg    g.c.clo     g.c.bet
 +LUKE             15 0.44680851 0.297278912
 +LEIA             12 0.42000000 0.217120181
 +C-3PO            10 0.40384615 0.057596372
 +HAN               8 0.38888889 0.176190476
 +CHEWBACCA         8 0.38888889 0.035487528
 +OBI-WAN           7 0.38181818 0.014852608
 +R2-D2             7 0.38181818 0.011904762
 +BIGGS             7 0.36842105 0.032142857
 +RED LEADER        7 0.36842105 0.032142857
 +BERU              4 0.35000000 0.005442177
 +DODONNA           5 0.34426230 0.011111111
 +GOLD LEADER       5 0.33870968 0.003174603
 +WEDGE             5 0.33870968 0.003174603
 +DARTH VADER       5 0.32812500 0.011904762
 +OWEN              3 0.32812500 0.000000000
 +CAMIE             2 0.32307692 0.000000000
 +RED TEN           2 0.32307692 0.000000000
 +MOTTI             3 0.31343284 0.000000000
 +TARKIN            3 0.31343284 0.000000000
 +GREEDO            1 0.28767123 0.000000000
 +JABBA             1 0.28767123 0.000000000
 +GOLD FIVE         0 0.04545455 0.000000000
 +> 
 +</code>
 +
 +<code>
 +g.c.bac <- distances(g, v=V(g)["R2-D2"], to=V(g), weights=NA)
 +g.c.bac
 +</code>
 +
 +<code>
 +> g.c.bac <- distances(g, v=V(g)["R2-D2"], to=V(g), weights=NA)
 +> g.c.bac
 +      R2-D2 CHEWBACCA C-3PO LUKE DARTH VADER CAMIE BIGGS LEIA BERU OWEN OBI-WAN MOTTI
 +R2-D2     0         1     1    1           2     2     2    1    2    2       1     2
 +      TARKIN HAN GREEDO JABBA DODONNA GOLD LEADER WEDGE RED LEADER RED TEN GOLD FIVE
 +R2-D2      2   1      2     2       1           2     2          2       2       Inf
 +</code>
  
r/social_network_analysis_tutorial.1574809992.txt.gz · Last modified: 2019/11/27 08:13 by hkimscil
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