I was wondering if you guys can help me building an adjacency matrix. I have data in CVS format like this:
Paper_ID Author
2 Foster-McGregor, N.
3 Van Houte, M.
4 van de Meerendonk, A.
5 Farla, K.
6 van Houte, M.
6 Siegel, M.
8 Farla, K.
11 Farla, K.
11 Verspagen, B.
As you can see the column "Paper_ID" has a repeated value of 11, meaning that "Farla, K." and "Verspagen, B." are coauthors of a publication. I need to build a square weighted matrix using the names of the authors, counting the times that they are collaborating together.
Does the following do what you are looking for?
# simulate data.
d <- data.frame(
id=c(2,3,4,5,6,6,8,11,11,12,12),
author=c("FN", "VM","VA","FK","VM","SM","FK","FK","VB","FK","VB")
)
d
id author
1 2 FN
2 3 VM
3 4 VA
4 5 FK
5 6 VM
6 6 SM
7 8 FK
8 11 FK
9 11 VB
10 12 FK
11 12 VB
# create incidence matrix:
m <- xtabs(~author+id,d)
m
id
author 2 3 4 5 6 8 11 12
FK 0 0 0 1 0 1 1 1
FN 1 0 0 0 0 0 0 0
SM 0 0 0 0 1 0 0 0
VA 0 0 1 0 0 0 0 0
VB 0 0 0 0 0 0 1 1
VM 0 1 0 0 1 0 0 0
# convert to adjacency matrix.
# tcrossprod does "m %*% t(m)"
tcrossprod(m)
author
author FK FN SM VA VB VM
FK 4 0 0 0 2 0
FN 0 1 0 0 0 0
SM 0 0 1 0 0 1
VA 0 0 0 1 0 0
VB 2 0 0 0 2 0
VM 0 0 1 0 0 2
Note that crossprod() will give you the incidence matrix for the id variable (i.e. will do t(m) %*% m).