44 research outputs found
Explosive Percolation: Unusual Transitions of a Simple Model
In this paper we review the recent advances on explosive percolation, a very
sharp phase transition first observed by Achlioptas et al. (Science, 2009).
There a simple model was proposed, which changed slightly the classical
percolation process so that the emergence of the spanning cluster is delayed.
This slight modification turns out to have a great impact on the percolation
phase transition. The resulting transition is so sharp that it was termed
explosive, and it was at first considered to be discontinuous. This surprising
fact stimulated considerable interest in "Achlioptas processes". Later work,
however, showed that the transition is continuous (at least for Achlioptas
processes on Erdos networks), but with very unusual finite size scaling. We
present a review of the field, indicate open "problems" and propose directions
for future research.Comment: 27 pages, 4 figures, Review pape
Evolution of Vocabulary on Scale-free and Random Networks
We examine the evolution of the vocabulary of a group of individuals
(linguistic agents) on a scale-free network, using Monte Carlo simulations and
assumptions from evolutionary game theory. It is known that when the agents are
arranged in a two-dimensional lattice structure and interact by diffusion and
encounter, then their final vocabulary size is the maximum possible. Knowing
all available words is essential in order to increase the probability to
``survive'' by effective reproduction. On scale-free networks we find a
different result. It is not necessary to learn the entire vocabulary available.
Survival chances are increased by using the vocabulary of the ``hubs'' (nodes
with high degree). The existence of the ``hubs'' in a scale-free network is the
source of an additional important fitness generating mechanism.Comment: 10 pages, 3 Figures, accepted in Physica
Statistical Mechanical Approach to Human Language
We use the formulation of equilibrium statistical mechanics in order to study
some important characteristics of language. Using a simple expression for the
Hamiltonian of a language system, which is directly implied by the Zipf law, we
are able to explain several characteristic features of human language that seem
completely unrelated, such as the universality of the Zipf exponent, the
vocabulary size of children, the reduced communication abilities of people
suffering from schizophrenia, etc. While several explanations are necessarily
only qualitative at this stage, we have, nevertheless, been able to derive a
formula for the vocabulary size of children as a function of age, which agrees
rather well with experimental data.Comment: 20 pages,4 figures, Accepted in Physica
“The value relevance of dividend announcement: An empirical study of the Greek Stock Market”
Purpose: Dividend policy and its impact on share pricing, has been an issue of great concern for the academic society. Over the years, many theories evolved in an effort to explain dividend policy impact on corporate value. A widely accepted approach is the signaling effect theory. The purpose of this paper is to assess the value relevance of dividend announcement. Design/methodology/approach: Our empirical work uses Greek stock market data. We adopt the event study methodology and incorporate in our research elements that differentiate Greek stock market from other developing markets. Findings: Our empirical results tend to support the theory. Decisions on dividend policy seem to affect corporate value. Investors perceive incremented dividend payments as an indication of positive future prospect and vice versa. Research limitations/implications: Different results between large and medium capitalization shares comprise an interesting element for future research
Language Time Series Analysis
We use the Detrended Fluctuation Analysis (DFA) and the Grassberger-Proccacia
analysis (GP) methods in order to study language characteristics. Despite that
we construct our signals using only word lengths or word frequencies, excluding
in this way huge amount of information from language, the application of
Grassberger- Proccacia (GP) analysis indicates that linguistic signals may be
considered as the manifestation of a complex system of high dimensionality,
different from random signals or systems of low dimensionality such as the
earth climate. The DFA method is additionally able to distinguish a natural
language signal from a computer code signal. This last result may be useful in
the field of cryptography.Comment: 21 pages, 5 figures, accepted in Physica
A Random Matrix Approach to Language Acquisition
Since language is tied to cognition, we expect the linguistic structures to
reflect patterns we encounter in nature and analyzed by physics. Within this
realm we investigate the process of protolanguage acquisition, using analytical
and tractable methods developed within physics. A protolanguage is a mapping
between sounds and objects (or concepts) of the perceived world. This mapping
is represented by a matrix and the linguistic interaction among individuals is
described by a random matrix model. There are two essential parameters in our
approach. The strength of the linguistic interaction , which following
Chomsky's tradition, we consider as a genetically determined ability, and the
number of employed sounds (the lexicon size). Our model of linguistic
interaction is analytically studied using methods of statistical physics and
simulated by Monte Carlo techniques. The analysis reveals an intricate
relationship between the innate propensity for language acquisition and
the lexicon size , . Thus a small increase of the
genetically determined may lead to an incredible lexical explosion. Our
approximate scheme offers an explanation for the biological affinity of
different species and their simultaneous linguistic disparity.Comment: 16 pages, 4 figures. Submitted to JSTA