  One of the most interesting scientific challenges nowadays deals with the
analysis and the understanding of complex networks' dynamics. A major issue is
the definition of new frameworks for the exploration of the dynamics at play in
real dynamic networks. Here, we focus on scientific communities by analyzing
the "social part" of Science through a descriptive approach that aims at
identifying the social determinants (e.g. goals and potential interactions
among individuals) behind the emergence and the resilience of scientific
communities. We consider that scientific communities are at the same time
communities of practice (through co-authorship) and that they exist also as
representations in the scientists' mind, since references to other scientists'
works is not merely an objective link to a relevant work, but it reveals social
objects that one manipulates and refers to. In this paper we identify the
patterns about the evolution of a scientific field by analyzing a portion of
the arXiv repository covering a period of 10 years of publications in physics.
As a citation represents a deliberative selection related to the relevance of a
work in its scientific domain, our analysis approaches the co-existence between
co-authorship and citation behaviors in a community by focusing on the most
proficient and cited authors interactions patterns. We focus in turn, on how
these patterns are affected by the selection process of citations. Such a
selection a) produces self-organization because it is played by a group of
individuals which act, compete and collaborate in a common environment in order
to advance Science and b) determines the success (emergence) of both topics and
scientists working on them. The dataset is analyzed a) at a global level, e.g.
the network evolution, b) at the meso-level, e.g. communities emergence, and c)
at a micro-level, e.g. nodes' aggregation patterns.
