Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Characterizing the head of the degree distributions of growing networks   The analysis in this paper helps to explain the formation of growing networks
with degree distributions that follow extended exponential or power-law tails.
We present a generic model in which edge dynamics are driven by a continuous
attachment of new nodes and a mixed attachment mechanism that triggers random
or preferential attachment. Furthermore, reciprocal edges to newly added nodes
are established according to a response mechanism. The proposed framework
extends previous mixed attachment models by allowing the number of new edges to
vary according to various discrete probability distributions, including
Poisson, Binomial, Zeta, and Log-Series. We derive analytical expressions for
the limit in-degree distribution that results from the mixed attachment and
response mechanisms. Moreover, we describe the evolution of the dynamics of the
cumulative in-degree distribution. Simulation results illustrate how the number
of new edges and the process of reciprocity significantly impact the head of
the degree distribution.

0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
19
The categories of this paper are: eess
22
The categories of this paper are: chao-dyn
1
The categories of this paper are: cs
9
The categories of this paper are: nlin
15
The categories of this paper are: nucl-ex
37
The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci
10
The categories of this paper are: q-bio
14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
4
The categories of this paper are: cond-mat
7
The categories of this paper are: hep-th
6
The categories of this paper are: astro-ph
23
The categories of this paper are: solv-int