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This is a back digest, missed ruing my hegira thru occupied America

   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
  _______________________________________________________________________
   NetLab Network                 FRSC                      INSNA Founder
   http://www.chass.utoronto.ca/~wellman           twitter: @barrywellman
   NETWORKED: The New Social Operating System  Lee Rainie & Barry Wellman
                        http://amzn.to/zXZg39
   _______________________________________________________________________


---------- Forwarded message ----------
Date: Mon, 27 Feb 2017 12:03:07 +0000
From: "[utf-8] Complexity Digest" <[log in to unmask]>
Reply-To: [log in to unmask]
To: "[utf-8] Barry" <[log in to unmask]>
Subject: [utf-8] Latest Complexity Digest Posts

Learn about the latest and greatest related to complex systems research. More at http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=e0a51e4a00&e=55e25a0e3e



Will Democracy Survive Big Data and Artificial Intelligence?

    http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=b585a252e5&e=55e25a0e3e

We are at the historic moment, where we have to decide on the right path˙˙a path that allows us all to benefit from the digital revolution. Therefore, we urge to adhere to the following fundamental principles:

1. to increasingly decentralize the function of information systems;

2. to support informational self-determination and participation;

3. to improve transparency in order to achieve greater trust;

4. to reduce the distortion and pollution of information;

5. to enable user-controlled information filters;

6. to support social and economic diversity;

7. to improve interoperability and collaborative opportunities;

8. to create digital assistants and coordination tools;

9. to support collective intelligence, and

10. to promote responsible behavior of citizens in the digital world through digital literacy and enlightenment.


Will Democracy Survive Big Data and Artificial Intelligence?
By Dirk Helbing, Bruno S. Frey, Gerd Gigerenzer, Ernst Hafen, Michael Hagner, Yvonne Hofstetter, Jeroen van den Hoven, Roberto V. Zicari, Andrej Zwitter on February 25, 2017

Scientific American

Source: www.scientificamerican.com (http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=86cef10f0f&e=55e25a0e3e)



Pathways towards instability in financial networks

    http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=a0a5785b48&e=55e25a0e3e

Following the financial crisis of 2007˙˙2008, a deep analogy between the origins of instability in financial systems and complex ecosystems has been pointed out: in both cases, topological features of network structures influence how easily distress can spread within the system. However, in financial network models, the details of how financial institutions interact typically play a decisive role, and a general understanding of precisely how network topology creates instability remains lacking. Here we show how processes that are widely believed to stabilize the financial system, that is, market integration and diversification, can actually drive it towards instability, as they contribute to create cyclical structures which tend to amplify financial distress, thereby undermining systemic stability and making large crises more likely. This result holds irrespective of the details of how institutions interact, showing that policy-relevant analysis of the factors affecting
financial stability can be carried out while abstracting away from such details.


Pathways towards instability in financial networks
Marco Bardoscia, Stefano Battiston, Fabio Caccioli & Guido Caldarelli
Nature Communications 8, Article number: 14416 (2017)
doi:10.1038/ncomms14416

Source: www.nature.com (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=696c4e562c&e=55e25a0e3e)





Identifying Critical States through the Relevance Index

    The identification of critical states is a major task in complex 
systems, and the availability of measures to detect such conditions is of 
utmost importance. In general, criticality refers to the existence of two 
qualitatively different behaviors that the same system can exhibit, 
depending on the values of some parameters. In this paper, we show that 
the relevance index may be effectively used to identify critical states in 
complex systems. The relevance index was originally developed to identify 
relevant sets of variables in dynamical systems, but in this paper, we 
show that it is also able to capture features of criticality. The index is 
applied to two prominent examples showing slightly different meanings of 
criticality, namely the Ising model and random Boolean networks. Results 
show that this index is maximized at critical states and is robust with 
respect to system size and sampling effort. It can therefore be used to 
detect criticality.


Identifying Critical States through the Relevance Index
Andrea Roli, Marco Villani, Riccardo Caprari and Roberto Serra

Entropy 2017, 19(2), 73; doi:10.3390/e19020073

Source: www.mdpi.com (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=502d60cf94&e=55e25a0e3e)



Bumblebees show cognitive flexibility by improving on an observed complex behavior

    One hallmark of cognitive complexity is the ability to manipulate objects with a specific goal in mind. Such ˙˙tool use˙˙ at one time was ascribed to humans alone, but then to primates, next to marine mammals, and later to birds. Now we recognize that many species have the capacity to envision how a particular object might be used to achieve an end. Loukola et al. extend this insight to invertebrates. Bumblebees were trained to see that a ball could be used to produce a reward. These bees then spontaneously rolled the ball when given the chance.

Source: science.sciencemag.org (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=d393c9971f&e=55e25a0e3e)



Thomas Crombie Schelling (1921˙˙2016)

    Thomas Schelling, the distinguished economist, died on 13 December 2016 at his home in Bethesda, Maryland. He was 95 years old. Schelling applied his prolific work in game theory to arms control and deterrence, negotiation strategy, and most recently, global warming. His strategic insights made the world a much safer place.


Thomas Crombie Schelling (1921˙˙2016)
Richard Zeckhauser

Science  24 Feb 2017:
Vol. 355, Issue 6327, pp. 800
DOI: 10.1126/science.aam9079

Source: science.sciencemag.org (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=a36f29c58d&e=55e25a0e3e)



Feasibility and coexistence of large ecological communities

    http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=a5645df811&e=55e25a0e3e

The role of species interactions in controlling the interplay between the stability of ecosystems and their biodiversity is still not well understood. The ability of ecological communities to recover after small perturbations of the species abundances (local asymptotic stability) has been well studied, whereas the likelihood of a community to persist when the conditions change (structural stability) has received much less attention. Our goal is to understand the effects of diversity, interaction strengths and ecological network structure on the volume of parameter space leading to feasible equilibria. We develop a geometrical framework to study the range of conditions necessary for feasible coexistence. We show that feasibility is determined by few quantities describing the interactions, yielding a nontrivial complexity˙˙feasibility relationship. Analysing more than 100 empirical networks, we show that the range of coexistence conditions in mutualistic systems can be
analytically predicted. Finally, we characterize the geometric shape of the feasibility domain, thereby identifying the direction of perturbations that are more likely to cause extinctions.

Source: www.nature.com (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=d032202c9b&e=55e25a0e3e)



Prediction limits of mobile phone activity modelling

    Thanks to their widespread usage, mobile devices have become one of the main sensors of human behaviour and digital traces left behind can be used as a proxy to study urban environments. Exploring the nature of the spatio-temporal patterns of mobile phone activity could thus be a crucial step towards understanding the full spectrum of human activities. Using 10 months of mobile phone records from Greater London resolved in both space and time, we investigate the regularity of human telecommunication activity on urban scales. We evaluate several options for decomposing activity timelines into typical and residual patterns, accounting for the strong periodic and seasonal components. We carry out our analysis on various spatial scales, showing that regularity increases as we look at aggregated activity in larger spatial units with more activity in them. We examine the statistical properties of the residuals and show that it can be explained by noise and specific outliers. Also,
we look at sources of deviations from the general trends, which we find to be explainable based on knowledge of the city structure and places of attractions. We show examples how some of the outliers can be related to external factors such as specific social events.


Prediction limits of mobile phone activity modelling
Dániel Kondor, Sebastian Grauwin, Zsófia Kallus, István Gódor, Stanislav Sobolevsky, Carlo Ratti

Royal Society Open Science

Feb 2017

Source: rsos.royalsocietypublishing.org (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=0729b22628&e=55e25a0e3e)


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Founding Editor: Gottfried Mayer.
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