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I used to watch the Grammys to celebrate my favorite songs/singers.
Now I watch to discover whom I don't know.

Selected Complexity Digest items below


Barry Wellman, FRSC               Director, NetLab Network
Founder, International Network for Social Network Analysis

Kyle Lowry is My Spirit Animal
Step by step, link by link, putting it together--Streisand/Sondheim
The earth to be spannd, connected by network--Walt Whitman
It's Always Something--Roseanne Roseannadanna
A day like all days, filled with those events that alter and illuminate our times--You Are There!

NETWORKED: The New Social Operating System  Lee Rainie & Barry Wellman    

-------- Forwarded Message --------
Subject: 	Latest Complexity Digest Posts
Date: 	Mon, 27 Jan 2020 12:01:44 +0000
From: 	Complexity Digest <[log in to unmask]>
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To: 	Barry <[log in to unmask]>

Learn about the latest and greatest related to complex systems research. 
More at 

Steven Strogatz Talks Science and Math on the Joy of x Podcast 

The noted mathematician and author Steven Strogatz explains why he 
wanted to share intimate conversations with leading researchers from 
diverse fields in his new Quanta Magazine podcast.

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Complex economic activities concentrate in large cities 

Pierre-Alexandre Balland, Cristian Jara-Figueroa, Sergio G. Petralia, 
Mathieu P. A. Steijn, David L. Rigby & César A. Hidalgo
Nature Human Behaviour (2020)

Human activities, such as research, innovation and industry, concentrate 
disproportionately in large cities. The ten most innovative cities in 
the United States account for 23% of the national population, but for 
48% of its patents and 33% of its gross domestic product. But why has 
human activity become increasingly concentrated? Here we use data on 
scientific papers, patents, employment and gross domestic product, for 
353 metropolitan areas in the United States, to show that the spatial 
concentration of productive activities increases with their complexity. 
Complex economic activities, such as biotechnology, neurobiology and 
semiconductors, concentrate disproportionately in a few large cities 
compared to less--complex activities, such as apparel or paper 
manufacturing. We use multiple proxies to measure the complexity of 
activities, finding that complexity explains from 40% to 80% of the 
variance in urban concentration of occupations, industries, scientific 
fields and technologies. Using
historical patent data, we show that the spatial concentration of 
cutting-edge technologies has increased since 1850, suggesting a 
reinforcing cycle between the increase in the complexity of activities 
and urbanization. These findings suggest that the growth of spatial 
inequality may be connected to the increasing complexity of the economy.

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Analysis and control of epidemics in temporal networks with 
self-excitement and behavioral changes

Lorenzo Zino, Alessandro . Rizzo, Maurizio Porfiri

European Journal of Control

The complexity of interaction patterns among individuals in social 
systems plays a fundamental role on the inception and spreading of 
epidemic outbreaks. Empirical evidence has shown that the network of 
social interactions may co-evolve with the spread of the disease at 
comparable time-scales. Time-varying features have also been documented 
in the study of the propensity of individuals toward social activity, 
leading to the emergence of burstiness and temporal clustering. These 
temporal network dynamics are not independent of the disease evolution, 
whereby infected individuals could experience changes in their tendency 
to form connections, spontaneously or due to exogenous control policies. 
Neglecting these phenomena in modeling epidemics could lead to dangerous 
mispredictions of an outbreak and ineffective control interventions. In 
this paper, we propose a mathematically tractable modeling framework 
that relies on a limited number of parameters and encapsulates all these 
instances of
complex phenomena through the lens of activity driven networks. Hawkes 
processes, Markov chains, and stability theory are leveraged to assist 
in the analysis of the framework and the formulation of theory-based 
control interventions. Our mathematical findings confirm the intuition 
that bursty activity patterns, typical of humans, facilitate epidemic 
spreading, while behavioral changes aiming at individual isolation could 
accelerate the eradication of epidemics. The proposed tools are 
demonstrated on a real-world case of influenza spreading in Italy. 
Overall, this work contributes new insight into the theory of temporal 
networks, laying the foundations for the analysis and control of 
spreading processes over networks with complex interaction patterns.

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Neural Dendrites Reveal Their Computational Power 

The dendritic arms of some human neurons can perform logic operations 
that once seemed to require whole neural networks.

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Mediterranean School of Complex Networks 2020 

Date: 5 Sep - 12 Sep 2020
Location: Salina, Sicily

In the last decade, network theory has been revealed to be a perfect 
instrument to model the structure of complex systems and the dynamical 
process they are involved into. The wide variety of applications to 
social sciences, technological networks, biology, transportation and 
economic, to cite just only some of them, showed that network theory is 
suitable to provide new insights into many problems.
Given the success of the Sixth Edition in 2019 of the Mediterranean 
School of Complex Networks, we call for applications to the Seventh 
Edition in 2020.

( )

Network experiment demonstrates converse symmetry breaking 

F. Molnar, T. Nishikawa, and A.E. Motter,
Nature Physics (2020), doi:10.1038/s41567-019-0742-y.

Symmetry breaking—the phenomenon in which the symmetry of a system is 
not inherited by its stable states—underlies pattern formation, 
superconductivity and numerous other effects. Recent theoretical work 
has established the possibility of converse symmetry breaking, a 
phenomenon in which the stable states are symmetric only when the system 
itself is not. This includes scenarios in which interacting entities are 
required to be non-identical in order to exhibit identical behaviour, 
such as in reaching consensus. Here we present an experimental 
demonstration of this phenomenon. Using a network of alternating-current 
electromechanical oscillators, we show that their ability to achieve 
identical frequency synchronization is enhanced when the oscillators are 
tuned to be suitably non-identical and that converse symmetry breaking 
persists for a range of noise levels. These results have implications 
for the optimization and control of network dynamics in a broad class of 
systems whose function
benefits from harnessing uniform behaviour.

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Sponsored by the Complex Systems Society.
Founding Editor: Gottfried Mayer.
Editor-in-Chief: Carlos Gershenson.

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