64,249 research outputs found
Networks based on collisions among mobile agents
We investigate in detail a recent model of colliding mobile agents [Phys.
Rev. Lett.~96, 088702], used as an alternative approach to construct evolving
networks of interactions formed by the collisions governed by suitable
dynamical rules. The system of mobile agents evolves towards a quasi-stationary
state which is, apart small fluctuations, well characterized by the density of
the system and the residence time of the agents. The residence time defines a
collision rate and by varying the collision rate, the system percolates at a
critical value, with the emergence of a giant cluster whose critical exponents
are the ones of two-dimensional percolation. Further, the degree and clustering
coefficient distributions and the average path length show that the network
associated with such a system presents non-trivial features which, depending on
the collision rule, enables one not only to recover the main properties of
standard networks, such as exponential, random and scale-free networks, but
also to obtain other topological structures. Namely, we show a specific example
where the obtained structure has topological features which characterize
accurately the structure and evolution of social networks in different
contexts, ranging from networks of acquaintances to networks of sexual
contacts.Comment: 12 pages, 17 figure
New approaches to model and study social networks
We describe and develop three recent novelties in network research which are
particularly useful for studying social systems. The first one concerns the
discovery of some basic dynamical laws that enable the emergence of the
fundamental features observed in social networks, namely the nontrivial
clustering properties, the existence of positive degree correlations and the
subdivision into communities. To reproduce all these features we describe a
simple model of mobile colliding agents, whose collisions define the
connections between the agents which are the nodes in the underlying network,
and develop some analytical considerations. The second point addresses the
particular feature of clustering and its relationship with global network
measures, namely with the distribution of the size of cycles in the network.
Since in social bipartite networks it is not possible to measure the clustering
from standard procedures, we propose an alternative clustering coefficient that
can be used to extract an improved normalized cycle distribution in any
network. Finally, the third point addresses dynamical processes occurring on
networks, namely when studying the propagation of information in them. In
particular, we focus on the particular features of gossip propagation which
impose some restrictions in the propagation rules. To this end we introduce a
quantity, the spread factor, which measures the average maximal fraction of
nearest neighbors which get in contact with the gossip, and find the striking
result that there is an optimal non-trivial number of friends for which the
spread factor is minimized, decreasing the danger of being gossiped.Comment: 16 Pages, 9 figure
A system of mobile agents to model social networks
We propose a model of mobile agents to construct social networks, based on a
system of moving particles by keeping track of the collisions during their
permanence in the system. We reproduce not only the degree distribution,
clustering coefficient and shortest path length of a large data base of
empirical friendship networks recently collected, but also some features
related with their community structure. The model is completely characterized
by the collision rate and above a critical collision rate we find the emergence
of a giant cluster in the universality class of two-dimensional percolation.
Moreover, we propose possible schemes to reproduce other networks of particular
social contacts, namely sexual contacts.Comment: Phys. Rev. Lett. (in press
The Dynamics of a Mobile Phone Network
The empirical study of network dynamics has been limited by the lack of
longitudinal data. Here we introduce a quantitative indicator of link
persistence to explore the correlations between the structure of a mobile phone
network and the persistence of its links. We show that persistent links tend to
be reciprocal and are more common for people with low degree and high
clustering. We study the redundancy of the associations between persistence,
degree, clustering and reciprocity and show that reciprocity is the strongest
predictor of tie persistence. The method presented can be easily adapted to
characterize the dynamics of other networks and can be used to identify the
links that are most likely to survive in the future
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