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Not as many network-related articles this week. Sandy's influence?
Hope all SOCNET members who are in the storm's path are safe, dry, and 
have fully charged electronics/functioning backup generators.

Dawn

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Natural networks as thermodynamic systems
Tuomo Hartonen1, Arto Annila1,2,3,*
Complexity

http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=9284eca378&e=d38efa683e 

Natural networks are considered as thermodynamic systems that evolve 
from one state to another by consuming free energy. The least-time 
consumption of free energy is found to result in ubiquitous scale-free 
characteristics. The network evolution will yield the scale-independent 
qualities because the least-time imperative will prefer attachment of 
nodes that contribute most to the free-energy consumption. The analysis 
of evolutionary equation of motion, derived from statistical physics of 
open systems, reveals that evolution of natural networks is a 
path-dependent and nondeterministic process. Despite the 
noncomputability of evolution, many mathematical models of networks can 
be recognized as approximations of the least-time process as well as 
many measures of networks can be appreciated as practical assessments of 
the system's thermodynamic status.


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The Scaling of Human Interactions with City Size
Markus Schläpfer, Luis M. A. Bettencourt, Mathias Raschke, Rob Claxton, 
Zbigniew Smoreda, Geoffrey B. West, Carlo Ratti

http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=92c3052463&e=d38efa683e 


The pace of life accelerates with city size, manifested in a per capita 
increase of almost all socioeconomic rates such as GDP, wages, violent 
crime or the transmission of certain contagious diseases. Here, we show 
that the structure and dynamics of the underlying network of human 
interactions provides a possible unifying mechanism for the origin of 
these pervasive regularities. By analyzing billions of anonymized call 
records from two European countries we find that human social 
interactions follow a superlinear scale-invariant relationship with city 
population size. This systematic acceleration of the interaction 
intensity takes place within specific constraints of social grouping. 
Together, these results provide a general microscopic basis for a deeper 
understanding of cities as co-located social networks in space and time, 
and of the emergent urban socioeconomic processes that characterize 
complex human societies.


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Identifying influential spreaders and efficiently estimating infection 
numbers in epidemic models: A walk counting approach
Frank Bauer and Joseph T. Lizier

Europhysics Letters, 99, 68007 doi:10.1209/0295-5075/99/68007

http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=7b7ec905b5&e=d38efa683e 


We introduce a new method to efficiently approximate the number of 
infections resulting from a given initially infected node in a network 
of susceptible individuals. Our approach is based on counting the number 
of possible infection walks of various lengths to each other node in the 
network. We analytically study the properties of our method, in 
particular demonstrating different forms for SIS and SIR disease 
spreading (e.g., under the SIR model our method counts self-avoiding 
walks). In comparison to existing methods to infer the spreading 
efficiency of different nodes in the network (based on degree, k-shell 
decomposition analysis and different centrality measures), our method 
directly considers the spreading process and, as such, is unique in 
providing estimation of actual numbers of infections. Crucially, in 
simulating infections on various real-world networks with the SIR model, 
we show that our walks-based method improves the inference of the 
effectiveness of nodes over a wide range of infection rates compared to 
existing methods. We also analyse the trade-off between estimate 
accuracy and computational cost, showing that the better accuracy here 
can still be obtained at a comparable computational cost to other methods.



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______________________________________
Dawn R. Gilpin, PhD
Walter Cronkite School of Journalism & Mass Communication
Arizona State University
[log in to unmask]
@drgilpin

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