Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Thresholding normally distributed data creates complex networks   Network data sets are often constructed by some kind of thresholding
procedure. The resulting networks frequently possess properties such as
heavy-tailed degree distributions, clustering, large connected components and
short average shortest path lengths. These properties are considered typical of
complex networks and appear in many contexts, prompting consideration of their
universality. Here we introduce a simple model for correlated relational data
and study the network ensemble obtained by thresholding it. We find that some,
but not all, of the properties associated with complex networks can be seen
after thresholding the correlated data, even though the underlying data are not
"complex". In particular, we observe heavy-tailed degree distributions, a large
numbers of triangles, and short path lengths, while we do not observe
non-vanishing clustering or community structure.

29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
22
The categories of this paper are: chao-dyn
8
The categories of this paper are: hep-ex
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
2
The categories of this paper are: math
28
The categories of this paper are: alg-geom
24
The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
25
The categories of this paper are: patt-sol
33
The categories of this paper are: plasm-ph
34
The categories of this paper are: chem-ph
36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas