Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Faster Algorithm for Betweenness Centrality Based on Adjacency
  Matrices   Betweenness centrality is essential in complex network analysis; it
characterizes the importance of nodes and edges in networks. It is a crucial
problem that exactly computes the betweenness centrality in large networks
faster, which urgently needs to be solved. We propose a novel algorithm for
betweenness centrality based on the parallel computing of adjacency matrices,
which is faster than the existing algorithms for large networks. The time
complexity of the algorithm is only related to the number of nodes in the
network, not the number of edges. Experimental evidence shows that the
algorithm is effective and efficient. This novel algorithm is faster than
Brandes' algorithm on small and dense networks and offers excellent solutions
for betweenness centrality index computing on large-scale complex networks.

18
The categories of this paper are: econ
32
The categories of this paper are: atom-ph
33
The categories of this paper are: plasm-ph
10
The categories of this paper are: q-bio
21
The categories of this paper are: adap-org
13
The categories of this paper are: quant-ph
2
The categories of this paper are: math
30
The categories of this paper are: q-alg
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
35
The categories of this paper are: mtrl-th
6
The categories of this paper are: astro-ph
3
The categories of this paper are: physics
9
The categories of this paper are: nlin
29
The categories of this paper are: funct-an
27
The categories of this paper are: comp-gas