The primary matrix used in social network analysis are the adjacency matrix or sociomatrix, and the incidence matrix.
References
Wasserman, S. and Faust, K. (1994). Social network analysis: Methods and applications. Cambridge University Press.
Examples
A <- matrix(c(
1, 1, 0, 0, -1,
1, 0, 0, 1, 1,
0, 0, NA, 1, 1,
0, 1, 1, 0, 1,
1, 1, 1, 1, 0
), byrow = TRUE, ncol = 5)
B <- matrix(c(
1, 0, 0,
1, 1, 0,
0, NA, 0,
0, 1, 0,
0, 1, 1
), byrow = TRUE, ncol = 3)
matrix_report(A)
#> The matrix A might have the following characteristics:
#> --> The vectors of the matrix are `numeric`
#> --> No names assigned to the rows of the matrix
#> --> No names assigned to the columns of the matrix
#> --> The matrix has negative elements (network is signed)
#> --> The matrix has NA elements
#> --> Matrix is asymmetric (network is directed)
#> --> The main diagonal is nonzero (the network has loops)
#> --> The matrix is square, 5 by 5
#> nodes arcs
#> [1,] 5 13
matrix_report(B)
#> The matrix A might have the following characteristics:
#> --> The vectors of the matrix are `numeric`
#> --> No names assigned to the rows of the matrix
#> --> No names assigned to the columns of the matrix
#> --> The matrix has NA elements
#> --> The matrix is rectangular, 3 by 5
#> nodes_rows nodes_columns incidence_lines
#> [1,] 3 5 6