23,953 research outputs found
Synchronization in complex networks
Synchronization processes in populations of locally interacting elements are
in the focus of intense research in physical, biological, chemical,
technological and social systems. The many efforts devoted to understand
synchronization phenomena in natural systems take now advantage of the recent
theory of complex networks. In this review, we report the advances in the
comprehension of synchronization phenomena when oscillating elements are
constrained to interact in a complex network topology. We also overview the new
emergent features coming out from the interplay between the structure and the
function of the underlying pattern of connections. Extensive numerical work as
well as analytical approaches to the problem are presented. Finally, we review
several applications of synchronization in complex networks to different
disciplines: biological systems and neuroscience, engineering and computer
science, and economy and social sciences.Comment: Final version published in Physics Reports. More information
available at http://synchronets.googlepages.com
The Web as an Adaptive Network: Coevolution of Web Behavior and Web Structure
Much is known about the complex network structure of the Web, and about behavioral dynamics on the Web. A number of studies address how behaviors on the Web are affected by different network topologies, whilst others address how the behavior of users on the Web alters network topology. These represent complementary directions of influence, but they are generally not combined within any one study. In network science, the study of the coupled interaction between topology and behavior, or state-topology coevolution, is known as 'adaptive networks', and is a rapidly developing area of research. In this paper, we review the case for considering the Web as an adaptive network and several examples of state-topology coevolution on the Web. We also review some abstract results from recent literature in adaptive networks and discuss their implications for Web Science. We conclude that adaptive networks provide a formal framework for characterizing processes acting 'on' and 'of' the Web, and offers potential for identifying general organizing principles that seem otherwise illusive in Web Scienc
Dynamics-Driven Evolution to Structural Heterogeneity in Complex Networks
The mutual influence of dynamics and structure is a central issue in complex
systems. In this paper we study by simulation slow evolution of network under
the feedback of a local-majority-rule opinion process. If performance-enhancing
local mutations have higher chances of getting integrated into its structure,
the system can evolve into a highly heterogeneous small-world with a global hub
(whose connectivity is proportional to the network size), strong local
connection correlations and power law-like degree distribution. Networks with
better dynamical performance are achieved if structural evolution occurs much
slower than the network dynamics. Structural heterogeneity of many biological
and social dynamical systems may also be driven by various dynamics-structure
coupling mechanisms.Comment: Figure 2 updated. Final version as appear in Physica
Effects of Time Horizons on Influence Maximization in the Voter Dynamics
In this paper we analyze influence maximization in the voter model with an
active strategic and a passive influencing party in non-stationary settings. We
thus explore the dependence of optimal influence allocation on the time
horizons of the strategic influencer. We find that on undirected heterogeneous
networks, for short time horizons, influence is maximized when targeting
low-degree nodes, while for long time horizons influence maximization is
achieved when controlling hub nodes. Furthermore, we show that for short and
intermediate time scales influence maximization can exploit knowledge of
(transient) opinion configurations. More in detail, we find two rules. First,
nodes with states differing from the strategic influencer's goal should be
targeted. Second, if only few nodes are initially aligned with the strategic
influencer, nodes subject to opposing influence should be avoided, but when
many nodes are aligned, an optimal influencer should shadow opposing influence.Comment: 22 page
Ergodic Randomized Algorithms and Dynamics over Networks
Algorithms and dynamics over networks often involve randomization, and
randomization may result in oscillating dynamics which fail to converge in a
deterministic sense. In this paper, we observe this undesired feature in three
applications, in which the dynamics is the randomized asynchronous counterpart
of a well-behaved synchronous one. These three applications are network
localization, PageRank computation, and opinion dynamics. Motivated by their
formal similarity, we show the following general fact, under the assumptions of
independence across time and linearities of the updates: if the expected
dynamics is stable and converges to the same limit of the original synchronous
dynamics, then the oscillations are ergodic and the desired limit can be
locally recovered via time-averaging.Comment: 11 pages; submitted for publication. revised version with fixed
technical flaw and updated reference
Modelling Opinion Formation with Physics Tools: Call for Closer Link with Reality
The growing field of studies of opinion formation using physical formalisms and computer simulation based tools suffers from relative lack of connection to the 'real world' societal behaviour. Such sociophysics research should aim at explaining observations or at proposing new ones. Unfortunately, this is not always the case, as many works concentrate more on the models themselves than on the social phenomena. Moreover, the simplifications proposed in simulations often sacrifice realism on the altar of computability. There are several ways to improve the value of the research, the most important by promoting truly multidisciplinary cooperation between physicists aiming to describe social phenomena and sociologists studying the phenomena in the field. In the specific case of modelling of opinion formation there are a few technical ideas which might bring the computer models much closer to reality, and therefore to improve the predictive value of the sociophysics approach.Methodology, Agent Based Social Simulation, Qualitative Analysis; Evidence; Conditions of Application
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