Glossary
SNA
Social Network Analysis.
G
a graph with vertices and edges.
V
vertex set in a graph.
E
edge set in a graph.
W
weighted adjacency matrix of a graph.
M
our layered model adjacency matrix of a graph.
1
the constant one vector.
d i
degree of ith vertex.
D
diagonal degree matrix of an adjacency matrix.
ˆ
D
modified diagonal total degree of signed graph.
L
unnormalized Laplacian matrix of a graph.
L sym
symmetric normalized Laplacian matrix.
L rw
random-walk normalized Laplacian matrix.
L dir
Chung’s directed combinatorial Laplacian matrix.
ˆ
L dir
Chung’s directed normalized Laplacian matrix.
L dsym
our directed symmetric normalized Laplacian matrix.
L drw
our directed random walk normalized Laplacian matrix.
¯
L
Kunegis’s unnormalized signed Laplacian matrix.
¯
L rw
Kunegis’s random-walk normalized signed Laplacian matrix.
¯
L sym
Kunegis’s symmetric normalized signed Laplacian matrix.
L sign
our unnormalized signed Laplacian matrix.
L sns
our simple normalized signed Laplacian matrix.
L bns
our balanced normalized signed Laplacian matrix.
RatioCut()
Kunegis’s signed ratio cut.
SRcut()
our defined signed ratio cut.
1
constant one vector.
R M
Rayleigh quotient of matrix M.
P
probability (random walk) matrix.
cut()
number of cut edges.
RatioCut()
ratio cut.
Ncut()
normalized cut.
CheegerCut()
Cheeger cut.
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