Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: What do we learn from correlations of local and global network
  properties?   In complex networks a common task is to identify the most important or
"central" nodes. There are several definitions, often called centrality
measures, which often lead to different results. Here we study extensively
correlations between four local and global measures namely the degree, the
shortest-path-betweenness, the random-walk betweenness and the subgraph
centrality on different random-network models like Erdos-Renyi, Small-World and
Barabasi-Albert as well as on different real networks like metabolic pathways,
social collaborations and computer networks. Correlations are quite different
between the real networks and the model networks questioning whether the models
really reflect all important properties of the real world.

30
The categories of this paper are: q-alg
1
The categories of this paper are: cs
8
The categories of this paper are: hep-ex
18
The categories of this paper are: econ
27
The categories of this paper are: comp-gas
16
The categories of this paper are: stat
25
The categories of this paper are: patt-sol
15
The categories of this paper are: nucl-ex
24
The categories of this paper are: dg-ga
13
The categories of this paper are: quant-ph
29
The categories of this paper are: funct-an
22
The categories of this paper are: chao-dyn
9
The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
21
The categories of this paper are: adap-org
6
The categories of this paper are: astro-ph