28 research outputs found
Market ecology of active and passive investors
We study the role of active and passive investors in an investment market
with uncertainties. Active investors concentrate on a single or a few stocks
with a given probability of determining the quality of them. Passive investors
spread their investment uniformly, resembling buying the market index. In this
toy market stocks are introduced as good and bad. If a stock receives
sufficient investment it will survive, otherwise die. Active players exert a
selective pressure since they can determine to an extent the investment
quality. We show that the active players provide the driving force whereas the
passive ones act as free riders. While their gains do not differ too much, we
show that the active players enjoy an edge. Their presence also provides better
gains to the passive players and stocks themselves.Comment: 16 pages, 4 figure
Sex-Oriented stable matchings of the Marriage Problem with correlated and incomplete information
In the Stable Marriage Problem two sets of agents must be paired according to
mutual preferences, which may happen to conflict. We present two
generalizations of its sex-oriented version, aiming to take into account
correlations between the preferences of agents and costly information. Their
effects are investigated both numerically and analytically.Comment: 5 pages, 2 figures, Proceedings of the NATO ARW on Application of
Physics in Economic Modelling, Prague 200
Number of loops of size h in growing scale-free networks
The hierarchical structure of scale-free networks has been investigated
focusing on the scaling of the number of loops of size h as a function
of the system size. In particular we have found the analytic expression for the
scaling of in the Barab\'asi-Albert (BA) scale-free network. We have
performed numerical simulations on the scaling law for in the BA
network and in other growing scale free networks, such as the bosonic network
(BN) and the aging nodes (AN) network. We show that in the bosonic network and
in the aging node network the phase transitions in the topology of the network
are accompained by a change in the scaling of the number of loops with the
system size.Comment: 4 pages, 3 figure
Quantitative description and modeling of real networks
In this letter we present data analysis and modeling of two particular cases
of study in the field of growing networks. We analyze WWW data set and
authorship collaboration networks in order to check the presence of correlation
in the data. The results are reproduced with a pretty good agreement through a
suitable modification of the standard AB model of network growth. In
particular, intrinsic relevance of sites plays a role in determining the future
degree of the vertex.Comment: 4 pages, 3 figure
Growing dynamics of Internet providers
In this paper we present a model for the growth and evolution of Internet providers. The model reproduces the data observed for the Internet connection as probed by tracing routes from different computers. This problem represents a paramount case of study for growth processes in general, but can also help in the understanding the properties of the Internet. Our main result is that this network can be reproduced by a self-organized interaction between users and providers that can rearrange in time. This model can then be considered as a prototype model for the class of phenomena of aggregation processes in social networks
Folksonomies and clustering in the collaborative system CiteULike
We analyze CiteULike, an online collaborative tagging system where users
bookmark and annotate scientific papers. Such a system can be naturally
represented as a tripartite graph whose nodes represent papers, users and tags
connected by individual tag assignments. The semantics of tags is studied here,
in order to uncover the hidden relationships between tags. We find that the
clustering coefficient reflects the semantical patterns among tags, providing
useful ideas for the designing of more efficient methods of data classification
and spam detection.Comment: 9 pages, 5 figures, iop style; corrected typo
Self-organized network evolution coupled to extremal dynamics
The interplay between topology and dynamics in complex networks is a
fundamental but widely unexplored problem. Here, we study this phenomenon on a
prototype model in which the network is shaped by a dynamical variable. We
couple the dynamics of the Bak-Sneppen evolution model with the rules of the
so-called fitness network model for establishing the topology of a network;
each vertex is assigned a fitness, and the vertex with minimum fitness and its
neighbours are updated in each iteration. At the same time, the links between
the updated vertices and all other vertices are drawn anew with a
fitness-dependent connection probability. We show analytically and numerically
that the system self-organizes to a non-trivial state that differs from what is
obtained when the two processes are decoupled. A power-law decay of dynamical
and topological quantities above a threshold emerges spontaneously, as well as
a feedback between different dynamical regimes and the underlying correlation
and percolation properties of the network.Comment: Accepted version. Supplementary information at
http://www.nature.com/nphys/journal/v3/n11/suppinfo/nphys729_S1.htm