Hello,
Maybe you can sample from the vertices
subv <- sample(V(G), 100)
and then use something like [1] (StackOverflow).
[1]https://stackoverflow.com/questions/23682113/creating-subgraph-using-igraph-in-r
Hope this helps,
Rui Barradas
Às 22:02 de 03/05/19, Drake Gossi escreveu:
Hello everyone,
How would I randomly select 100 nodes to look at out of these approx.
25,0000? I'm practicing constructing a citation network.
edgeList below is an edge list.
head (edgeList)
to from
[1,] "4US6" "3US320"
[2,] "4US6" "4US1"
[3,] "6US280" "1US393"
[4,] "6US280" "1US53"
[5,] "6US280" "3US133"
[6,] "14US179" "5US321"
G <- graph.edgelist(edgeList, directed=FALSE)
G
IGRAPH a473ce7 UN-- 25417 216738 --
+ attr: name (v/c)
+ edges from a473ce7 (vertex names):
[1] 4US6 --3US320 4US6 --4US1 6US280 --1US393
[4] 6US280 --1US53 6US280 --3US133 14US179--5US321
[7] 14US179--9US262 15US45 --3US384 15US45 --4US436
[10] 15US45 --4US441 15US45 --8US421 15US227--13US388
[13] 15US227--2US36 15US290--7US220 9US262 --15US290
[16] 15US369--11US504 15US369--11US577 15US369--5US137
[19] 15US369--9US115 15US396--1US371 15US396--4US450
[22] 15US396--6US358 15US396--7US73 16US1 --11US603
+ ... omitted several edges
Can I use the sample () function? I'm working with the text Humanities
Data in R (Arnold & Tilton). I'm working within the igraph library.
Drake
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