6 research outputs found
Structural transitions in scale-free networks
Real growing networks like the WWW or personal connection based networks are
characterized by a high degree of clustering, in addition to the small-world
property and the absence of a characteristic scale. Appropriate modifications
of the (Barabasi-Albert) preferential attachment network growth capture all
these aspects. We present a scaling theory to describe the behavior of the
generalized models and the mean field rate equation for the problem. This is
solved for a specific case with the result C(k) ~ 1/k for the clustering of a
node of degree k. Numerical results agree with such a mean-field exponent which
also reproduces the clustering of many real networks.Comment: 4 pages, 3 figures, RevTex forma
Correlated dynamics in egocentric communication networks
We investigate the communication sequences of millions of people through two
different channels and analyze the fine grained temporal structure of
correlated event trains induced by single individuals. By focusing on
correlations between the heterogeneous dynamics and the topology of egocentric
networks we find that the bursty trains usually evolve for pairs of individuals
rather than for the ego and his/her several neighbors thus burstiness is a
property of the links rather than of the nodes. We compare the directional
balance of calls and short messages within bursty trains to the average on the
actual link and show that for the trains of voice calls the imbalance is
significantly enhanced, while for short messages the balance within the trains
increases. These effects can be partly traced back to the technological
constrains (for short messages) and partly to the human behavioral features
(voice calls). We define a model that is able to reproduce the empirical
results and may help us to understand better the mechanisms driving technology
mediated human communication dynamics.Comment: 7 pages, 6 figure