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SOCNET  February 2016

SOCNET February 2016

Subject:

selected Latest Complexity Digest Posts (fwd)

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Mon, 22 Feb 2016 17:09:36 -0500

Content-Type:

MULTIPART/MIXED

Parts/Attachments:

Parts/Attachments

TEXT/PLAIN (125 lines)

*****  To join INSNA, visit http://www.insna.org  *****

selected

   Barry Wellman
    A vision is just a vision if it's only in your head
    Step by step, link by link, putting it together
                  Streisand/Sondheim
  _______________________________________________________________________
   Visiting Prof         Schl of Information        University of Arizona
   NetLab Network                 FRSC                      INSNA Founder
   http://www.chass.utoronto.ca/~wellman           twitter: @barrywellman
   NETWORKED:The New Social Operating System   Lee Rainie & Barry Wellman
   MIT Press            http://amzn.to/zXZg39       Print $18  Kindle $11
   _______________________________________________________________________


Learn about the latest and greatest related to complex systems research. More at http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=6240a2ab87&e=55e25a0e3e

Universal resilience patterns in complex networks

    Resilience, a system˙˙s ability to adjust its activity to retain its basic functionality when errors, failures and environmental changes occur, is a defining property of many complex systems. Despite widespread consequences for human health, the economy and the environment, events leading to loss of resilience˙˙from cascading failures in technological systems to mass extinctions in ecological networks˙˙are rarely predictable and are often irreversible. These limitations are rooted in a theoretical gap: the current analytical framework of resilience is designed to treat low-dimensional models with a few interacting components, and is unsuitable for multi-dimensional systems consisting of a large number of components that interact through a complex network. Here we bridge this theoretical gap by developing a set of analytical tools with which to identify the natural control and state parameters of a multi-dimensional complex system, helping us derive effective one-dimensional
dynamics that accurately predict the system˙˙s resilience. The proposed analytical framework allows us systematically to separate the roles of the system˙˙s dynamics and topology, collapsing the behaviour of different networks onto a single universal resilience function. The analytical results unveil the network characteristics that can enhance or diminish resilience, offering ways to prevent the collapse of ecological, biological or economic systems, and guiding the design of technological systems resilient to both internal failures and environmental changes.

Universal resilience patterns in complex networks
Jianxi Gao, Baruch Barzel & Albert-László Barabási

Nature 530, 307˙˙312 (18 February 2016) http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=ff0f0f3710&e=55e25a0e3e
Complexity Digest's insight:

See Also http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=30d39b15e7&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=956ab69c18&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=19fdf96ee0&e=55e25a0e3e)


The likely determines the unlikely

    We point out that the functional form describing the frequency of sizes 
of events in complex systems (e.g. earthquakes, forest fires, bursts of 
neuronal activity) can be obtained from maximal likelihood inference, 
which, remarkably, only involve a few available observed measures such as 
number of events, total event size and extremes. Most importantly, the 
method is able to predict with high accuracy the frequency of the rare 
extreme events. To be able to predict the few, often big impact events, 
from the frequent small events is of course of great general importance. 
For a data set of wind speed we are able to predict the frequency of gales 
with good precision. We analyse several examples ranging from the shortest 
length of a recruit to the number of Chinese characters which occur only 
once in a text.

The likely determines the unlikely
Xiaoyong Yan, Petter Minnhagen, Henrik Jeldtoft Jensen

http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=ffa6ad34b3&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=db6f4f89b2&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=36cf8ee0f8&e=55e25a0e3e)



The International Postal Network and Other Global Flows As Proxies for National Wellbeing

    The digital exhaust left by flows of physical and digital commodities provides a rich measure of the nature, strength and significance of relationships between countries in the global network. With this work, we examine how these traces and the network structure can reveal the socioeconomic profile of different countries. We take into account multiple international networks of physical and digital flows, including the previously unexplored international postal network. By measuring the position of each country in the Trade, Postal, Migration, International Flights, IP and Digital Communications networks, we are able to build proxies for a number of crucial socioeconomic indicators such as GDP per capita and the Human Development Index ranking along with twelve other indicators used as benchmarks of national wellbeing by the United Nations and other international organisations. In this context, we have also proposed and evaluated a global connectivity degree measure applying
multiplex theory across the six networks that accounts for the strength of relationships between countries. We conclude with a multiplex community analysis of the global flow networks, showing how countries with shared community membership over multiple networks have similar socioeconomic profiles. Combining multiple flow data sources into global multiplex networks can help understand the forces which drive economic activity on a global level. Such an ability to infer proxy indicators in a context of incomplete information is extremely timely in light of recent discussions on measurement of indicators relevant to the Sustainable Development Goals.

The International Postal Network and Other Global Flows As Proxies for National Wellbeing
Desislava Hristova, Alex Rutherford, Jose Anson, Miguel Luengo-Oroz, Cecilia Mascolo

http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=fdac7e70b4&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=f13fdc2e20&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=7c4968d26b&e=55e25a0e3e)



Tensegrity, Dynamic Networks, and Complex Systems Biology: Emergence in Structural and Information Networks Within Living Cells

    The genomic revolution has led to the systematic characterization of all the genes of the genome and the proteins they encode. But we still do not fully understand how many cell behaviors are controlled, because many important biological properties of cells emerge at the whole-system level from the collective action of thousands of molecular components, which is orchestrated through specific regulatory interactions. In this chapter we present two distinct approaches based on the concept of molecular networks to understand two fundamental system properties of living cells: their ability to maintain their shape and mechanical stability, and their ability to express stable, discrete cell phenotypes and switch between them. We first describe how structural networks built using the principles of tensegrity architecture and computational models that incorporate these features can predict many of the complex mechanical behaviors that are exhibited by living mammalian cells. We then
discuss how genome-wide biochemical signaling networks produce ˙˙attractor˙˙ states that may represent the stable cell phenotypes, such as growth, differentiation, and apoptosis, and which explain how cells can make discrete cell fate decisions in the presence of multiple conflicting signals. These network-based concepts help to bridge the apparent gap between emergent system features characteristic of living cells and the underlying molecular processes.

Tensegrity, Dynamic Networks, and Complex Systems Biology: Emergence in Structural and Information Networks Within Living Cells
Sui Huang, Cornel Sultan, Donald E. Ingber


Human Atlas: A Tool for Mapping Social Networks

    Most social network analyses focus on online social networks. While 
these networks encode important aspects of our lives they fail to capture 
many real-world connections. Most of these connections are, in fact, 
public and known to the members of the community. Mapping them is a task 
very suitable for crowdsourcing: it is easily broken down in many simple 
and independent subtasks. Due to the nature of social networks -- presence 
of highly connected nodes and tightly knit groups -- if we allow users to 
map their immediate connections and the connections between them, we will 
need few participants to map most connections within a community. To this 
end, we built the Human Atlas, a web-based tool for mapping social 
networks. To test it, we partially mapped the social network of the MIT 
Media Lab. We ran a user study and invited members of the community to use 
the tool. In 4.6 man-hours, 22 participants mapped 984 connections within 
the lab, demonstrating the potential of the tool.

Human Atlas: A Tool for Mapping Social Networks
Martin Saveski, Eric Chu, Soroush Vosoughi, Deb Roy

http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=de92a9cf77&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=f42d870ab5&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=d9f5ab0050&e=55e25a0e3e)



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

You can contribute to Complexity Digest selecting one of our topics (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=108f7444e7&e=55e25a0e3e ) and using the "Suggest" button.
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