Abstract | ||
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One of the most interesting scientific challenges nowadays deals with the
analysis and the understanding of complex networks' dynamics and how their
processes lead to emergence according to the interactions among their
components. In this paper we approach the definition of new methodologies for
the visualization and the exploration of the dynamics at play in real dynamic
social networks. We present a recently introduced formalism called TVG (for
time-varying graphs), which was initially developed to model and analyze
highly-dynamic and infrastructure-less communication networks such as mobile
ad-hoc networks, wireless sensor networks, or vehicular networks. We discuss
its applicability to complex networks in general, and social networks in
particular, by showing how it enables the specification and analysis of complex
dynamic phenomena in terms of temporal interactions, and allows to easily
switch the perspective between local and global dynamics. As an example, we
chose the case of scientific communities by analyzing portion of the ArXiv
repository (ten years of publications in physics) focusing on 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,
select and refers to. In the paper we show the emergence/selection of a
community as a goal-driven preferential attachment toward a set of authors
among which there are some key scientists (Nobel prizes). |
Year | Keywords | Field |
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2011 | scientic commu- nities,social networks analysis,social selection.,evolving structures,time-varying graphs,temporal metrics,emergence,mobile ad hoc network,complex dynamics,complex network,social network,social network analysis,wireless sensor network | Dynamic network analysis,Interdependence,Data mining,Computer science,Visualization,Goal orientation,Citation,Complex network,Artificial intelligence,Formalism (philosophy),Machine learning,Preferential attachment |
DocType | Volume | Citations |
Journal | abs/1102.0 | 3 |
PageRank | References | Authors |
0.52 | 13 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Walter Quattrociocchi | 1 | 582 | 42.16 |
Frédéric Amblard | 2 | 430 | 51.43 |