1,805 research outputs found
Role-similarity based functional prediction in networked systems: Application to the yeast proteome
We propose a general method to predict functions of vertices where: 1. The
wiring of the network is somehow related to the vertex functionality. 2. A
fraction of the vertices are functionally classified. The method is influenced
by role-similarity measures of social network analysis. The two versions of our
prediction scheme is tested on model networks were the functions of the
vertices are designed to match their network surroundings. We also apply these
methods to the proteome of the yeast Saccharomyces cerevisiae and find the
results compatible with more specialized methods
Are Opinions Based on Science: Modelling Social Response to Scientific Facts
As scientists we like to think that modern societies and their members base
their views, opinions and behaviour on scientific facts. This is not
necessarily the case, even though we are all (over-) exposed to information
flow through various channels of media, i.e. newspapers, television, radio,
internet, and web. It is thought that this is mainly due to the conflicting
information on the mass media and to the individual attitude (formed by
cultural, educational and environmental factors), that is, one external factor
and another personal factor. In this paper we will investigate the dynamical
development of opinion in a small population of agents by means of a
computational model of opinion formation in a co-evolving network of socially
linked agents. The personal and external factors are taken into account by
assigning an individual attitude parameter to each agent, and by subjecting all
to an external but homogeneous field to simulate the effect of the media. We
then adjust the field strength in the model by using actual data on scientific
perception surveys carried out in two different populations, which allow us to
compare two different societies. We interpret the model findings with the aid
of simple mean field calculations. Our results suggest that scientifically
sound concepts are more difficult to acquire than concepts not validated by
science, since opposing individuals organize themselves in close communities
that prevent opinion consensus.Comment: 21 pages, 5 figures. Submitted to PLoS ON
The diplomat's dilemma: Maximal power for minimal effort in social networks
Closeness is a global measure of centrality in networks, and a proxy for how
influential actors are in social networks. In most network models, and many
empirical networks, closeness is strongly correlated with degree. However, in
social networks there is a cost of maintaining social ties. This leads to a
situation (that can occur in the professional social networks of executives,
lobbyists, diplomats and so on) where agents have the conflicting objectives of
aiming for centrality while simultaneously keeping the degree low. We
investigate this situation in an adaptive network-evolution model where agents
optimize their positions in the network following individual strategies, and
using only local information. The strategies are also optimized, based on the
success of the agent and its neighbors. We measure and describe the time
evolution of the network and the agents' strategies.Comment: Submitted to Adaptive Networks: Theory, Models and Applications, to
be published from Springe
Nonlocal evolution of weighted scale-free networks
We introduce the notion of globally updating evolution for a class of
weighted networks, in which the weight of a link is characterized by the amount
of data packet transport flowing through it. By noting that the packet
transport over the network is determined nonlocally, this approach can explain
the generic nonlinear scaling between the strength and the degree of a node. We
demonstrate by a simple model that the strength-driven evolution scheme
recently introduced can be generalized to a nonlinear preferential attachment
rule, generating the power-law behaviors in degree and in strength
simultaneously.Comment: 4 pages, 4 figures, final version published in PR
The networked seceder model: Group formation in social and economic systems
The seceder model illustrates how the desire to be different than the average
can lead to formation of groups in a population. We turn the original, agent
based, seceder model into a model of network evolution. We find that the
structural characteristics our model closely matches empirical social networks.
Statistics for the dynamics of group formation are also given. Extensions of
the model to networks of companies are also discussed
The dependence of strange hadron multiplicities on the speed of hadronization
Hadron multiplicities are calculated in the ALCOR model for the Pb+Pb
collisions at CERN SPS energy. Considering the newest experimental results, we
display our prediction obtained from the ALCOR model for stable hadrons
including strange baryons and anti-baryons.Comment: 8 pages, LaTeX in IOP style, appeared in the Proceedings of
Strangeness'97 Conference, Santorini, April 14-18 1997, J. of Physics G23
(1997) 194
Strangeness counting in high energy collisions
The estimates of overall strange quark production in high energy e+e-, pp and
ppbar collisions by using the statistical-thermal model of hadronisation are
presented and compared with previous works. The parametrization of strangeness
suppression within the model is discussed. Interesting regularities emerge in
the strange/non-strange produced quark ratio which turns out to be fairly
constant in elementary collisions while it is twice as large in SPS heavy ion
collision.Comment: talk given at Strangeness in Quark Matter 98, submitted to J. Phys.
Zero Temperature Glass Transition in the Two-Dimensional Gauge Glass Model
We investigate dynamic scaling properties of the two-dimensional gauge glass
model for the vortex glass phase in superconductors with quenched disorder.
From extensive Monte Carlo simulations we obtain static and dynamic finite
size scaling behavior, where the static simulations use a temperature exchange
method to ensure convergence at low temperatures. Both static and dynamic
scaling of Monte Carlo data is consistent with a glass transition at zero
temperature. We study a dynamic correlation function for the superconducting
order parameter, as well as the phase slip resistance. From the scaling of
these two functions, we find evidence for two distinct diverging correlation
times at the zero temperature glass transition. The longer of these time scales
is associated with phase slip fluctuations across the system that lead to
finite resistance at any finite temperature, while the shorter time scale is
associated with local phase fluctuations.Comment: 8 pages, 10 figures; v2: some minor correction
Dynamic scaling regimes of collective decision making
We investigate a social system of agents faced with a binary choice. We
assume there is a correct, or beneficial, outcome of this choice. Furthermore,
we assume agents are influenced by others in making their decision, and that
the agents can obtain information that may guide them towards making a correct
decision. The dynamic model we propose is of nonequilibrium type, converging to
a final decision. We run it on random graphs and scale-free networks. On random
graphs, we find two distinct regions in terms of the "finalizing time" -- the
time until all agents have finalized their decisions. On scale-free networks on
the other hand, there does not seem to be any such distinct scaling regions
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