9,431 research outputs found
Do extremists impose the structure of social networks?
The structure and the properties of complex networks essentially depend on
the way how nodes get connected to each other. We assume here that each node
has a feature which attracts the others. We model the situation by assigning
two numbers to each node, \omega and \alpha, where \omega indicates some
property of the node and \alpha the affinity towards that property. A node A is
more likely to establish a connection with a node B if B has a high value of
\omega and A has a high value of \alpha. Simple computer simulations show that
networks built according to this principle have a degree distribution with a
power law tail, whose exponent is determined only by the nodes with the largest
value of the affinity \alpha (the "extremists"). This means that the extremists
lead the formation process of the network and manage to shape the final
topology of the system. The latter phenomenon may have implications in the
study of social networks and in epidemiology.Comment: 4 pages, 3 figure
A simple model for the kinetics of packaging of DNA in to a capsid against an external force
We propose a simple model for the kinetics of packaging of viral DNA in to a
capsid against an external force trying to prevent it. The model leads to a
Butler-Volmer type dependence of the rate of packaging on the pulling force F
On the Consensus Threshold for the Opinion Dynamics of Krause-Hegselmann
In the consensus model of Krause-Hegselmann, opinions are real numbers
between 0 and 1 and two agents are compatible if the difference of their
opinions is smaller than the confidence bound parameter \epsilon. A randomly
chosen agent takes the average of the opinions of all neighbouring agents which
are compatible with it. We propose a conjecture, based on numerical evidence,
on the value of the consensus threshold \epsilon_c of this model. We claim that
\epsilon_c can take only two possible values, depending on the behaviour of the
average degree d of the graph representing the social relationships, when the
population N goes to infinity: if d diverges when N goes to infinity,
\epsilon_c equals the consensus threshold \epsilon_i ~ 0.2 on the complete
graph; if instead d stays finite when N goes to infinity, \epsilon_c=1/2 as for
the model of Deffuant et al.Comment: 15 pages, 7 figures, to appear in International Journal of Modern
Physics C 16, issue 2 (2005
The Sznajd Consensus Model with Continuous Opinions
In the consensus model of Sznajd, opinions are integers and a randomly chosen
pair of neighbouring agents with the same opinion forces all their neighbours
to share that opinion. We propose a simple extension of the model to continuous
opinions, based on the criterion of bounded confidence which is at the basis of
other popular consensus models. Here the opinion s is a real number between 0
and 1, and a parameter \epsilon is introduced such that two agents are
compatible if their opinions differ from each other by less than \epsilon. If
two neighbouring agents are compatible, they take the mean s_m of their
opinions and try to impose this value to their neighbours. We find that if all
neighbours take the average opinion s_m the system reaches complete consensus
for any value of the confidence bound \epsilon. We propose as well a weaker
prescription for the dynamics and discuss the corresponding results.Comment: 11 pages, 4 figures. To appear in International Journal of Modern
Physics
Universality of the Threshold for Complete Consensus for the Opinion Dynamics of Deffuant et al
In the compromise model of Deffuant et al., opinions are real numbers between
0 and 1 and two agents are compatible if the difference of their opinions is
smaller than the confidence bound parameter \epsilon. The opinions of a
randomly chosen pair of compatible agents get closer to each other. We provide
strong numerical evidence that the threshold value of \epsilon above which all
agents share the same opinion in the final configuration is 1/2, independently
of the underlying social topology.Comment: 8 pages, 4 figures, to appear in Int. J. Mod. Phys. C 15, issue
The dynamics of loop formation in a semiflexible polymer
The dynamics of loop formation by linear polymer chains has been a topic of
several theoretical/experimental studies. Formation of loops and their opening
are key processes in many important biological processes. Loop formation in
flexible chains has been extensively studied by many groups. However, in the
more realistic case of semiflexible polymers, not much results are available.
In a recent study (K. P. Santo and K. L. Sebastian, Phys. Rev. E, \textbf{73},
031293 (2006)), we investigated opening dynamics of semiflexible loops in the
short chain limit and presented results for opening rates as a function of the
length of the chain. We presented an approximate model for a semiflexible
polymer in the rod limit, based on a semiclassical expansion of the bending
energy of the chain. The model provided an easy way to describe the dynamics.
In this paper, using this model, we investigate the reverse process, i.e., the
loop formation dynamics of a semiflexible polymer chain by describing the
process as a diffusion-controlled reaction. We perform a detailed
multidimensional analysis of the problem and calculate closing times for a
semiflexible chain which leads to results that are physically expected. Such a
multidimensional analysis leading to these results does not seem to exist in
the literature so far.Comment: 37 pages 4 figure
Diffusion of scientific credits and the ranking of scientists
Recently, the abundance of digital data enabled the implementation of graph
based ranking algorithms that provide system level analysis for ranking
publications and authors. Here we take advantage of the entire Physical Review
publication archive (1893-2006) to construct authors' networks where weighted
edges, as measured from opportunely normalized citation counts, define a proxy
for the mechanism of scientific credit transfer. On this network we define a
ranking method based on a diffusion algorithm that mimics the spreading of
scientific credits on the network. We compare the results obtained with our
algorithm with those obtained by local measures such as the citation count and
provide a statistical analysis of the assignment of major career awards in the
area of Physics. A web site where the algorithm is made available to perform
customized rank analysis can be found at the address
http://www.physauthorsrank.orgComment: Revised version. 11 pages, 10 figures, 1 table. The portal to compute
the rankings of scientists is at http://www.physauthorsrank.or
Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities
Many complex networks display a mesoscopic structure with groups of nodes
sharing many links with the other nodes in their group and comparatively few
with nodes of different groups. This feature is known as community structure
and encodes precious information about the organization and the function of the
nodes. Many algorithms have been proposed but it is not yet clear how they
should be tested. Recently we have proposed a general class of undirected and
unweighted benchmark graphs, with heterogenous distributions of node degree and
community size. An increasing attention has been recently devoted to develop
algorithms able to consider the direction and the weight of the links, which
require suitable benchmark graphs for testing. In this paper we extend the
basic ideas behind our previous benchmark to generate directed and weighted
networks with built-in community structure. We also consider the possibility
that nodes belong to more communities, a feature occurring in real systems,
like, e. g., social networks. As a practical application, we show how
modularity optimization performs on our new benchmark.Comment: 9 pages, 13 figures. Final version published in Physical Review E.
The code to create the benchmark graphs can be freely downloaded from
http://santo.fortunato.googlepages.com/inthepress
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