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

Is it Rodney King and the Kent State massacre all over again? Hope not.

===================

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

Bit by bit, putting it together--Sondheim
It's Always Something--Roseanne Roseannadanna

Getting It Done; Getting It Out: A Practical Guide to Writing, Editing, Presenting and Promoting in the Social Sciences--coming in 2021 (we hope)

NETWORKED: The New Social Operating System  Lee Rainie & Barry Wellman http://amzn.to/zXZg39
http://www.chass.utoronto.ca/~wellman            https://en.wikipedia.org/wiki/Barry_Wellman


-------- Forwarded Message --------
Subject: Latest Complexity Digest Posts
Date: Mon, 1 Jun 2020 11:03:18 +0000
From: Complexity Digest <[log in to unmask]>
Reply-To: [log in to unmask]
To: Barry <[log in to unmask]>


Learn about the latest and greatest related to complex systems research. More at https://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=3c055209b2&e=55e25a0e3e



The epic battle against coronavirus misinformation and conspiracy theories

https://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=4fb84b86b4&e=55e25a0e3e

By studying the sources and spread of false information about COVID-19, researchers hope to understand where such information comes from, how it grows and — they hope — how to elevate facts over falsehood. It’s a battle that can’t be won completely, researchers agree — it’s not possible to stop people from spreading ill-founded rumours. But in the language of epidemiology, the hope is to come up with effective strategies to ‘flatten the curve’ of the infodemic, so that bad information can’t spread as far and as fast.

Source: www.nature.com (https://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=cbf15d76ce&e=55e25a0e3e)



The information theory of individuality

David Krakauer, Nils Bertschinger, Eckehard Olbrich, Jessica C. Flack & Nihat Ay
Theory in Biosciences volume 139, pages209–223(2020)


Despite the near universal assumption of individuality in biology, there is little agreement about what individuals are and few rigorous quantitative methods for their identification. Here, we propose that individuals are aggregates that preserve a measure of temporal integrity, i.e., “propagate” information from their past into their futures. We formalize this idea using information theory and graphical models. This mathematical formulation yields three principled and distinct forms of individuality—an organismal, a colonial, and a driven form—each of which varies in the degree of environmental dependence and inherited information. This approach can be thought of as a Gestalt approach to evolution where selection makes figure-ground (agent–environment) distinctions using suitable information-theoretic lenses. A benefit of the approach is that it expands the scope of allowable individuals to include adaptive aggregations in systems that are multi-scale, highly distributed, and do not
necessarily have physical boundaries such as cell walls or clonal somatic tissue. Such individuals might be visible to selection but hard to detect by observers without suitable measurement principles. The information theory of individuality allows for the identification of individuals at all levels of organization from molecular to cultural and provides a basis for testing assumptions about the natural scales of a system and argues for the importance of uncertainty reduction through coarse-graining in adaptive systems.

Source: link.springer.com (https://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=dec21a6647&e=55e25a0e3e)


Complex Systems: A Communication Networks Perspective Towards 6G

https://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=269f1b0c31&e=55e25a0e3e

Charalampos Sergiou ; Marios Lestas ; Pavlos Antoniou ; Christos Liaskos ; Andreas Pitsillides

IEEE Access ( Volume: 8 )


Over the last few years, the analysis and modeling of networks as well as the analysis and modeling of networked dynamical systems, has attracted considerable interdisciplinary interest, especially using the complex systems theory. These efforts are driven by the fact that systems, as diverse as genetic networks or the Internet can be effectively described as complex networks. Contrary, despite the unprecedented evolution of technology, basic issues and fundamental principles related to the structural and evolutionary properties of communication networks still remain largely unaddressed. The situation is even more complicated when we attempt to model the mobile communication networks and especially the 5th generation (5G) and eventually the forthcoming 6th generation (6G). In this work, we attempt to review basic models of complex networks from a communication networks perspective, focusing on their structural and evolutionary properties. Based on this review we aim to reveal the models of
complex networks, that may apply when modeling the 5G and 6G mobile communication networks. Furthermore, we expect to encourage the collaboration between complex systems and networking theorists toward meeting the challenging demands of 5G networks and beyond.

Source: ieeexplore.ieee.org (https://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=a6e37a1c21&e=55e25a0e3e)



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Founding Editor: Gottfried Mayer.
Editor-in-Chief: Carlos Gershenson.

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