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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    

-------- Forwarded Message --------
Subject: 	Latest Complexity Digest Posts
Date: 	Mon, 1 Jun 2020 11:03:18 +0000
From: 	Complexity Digest <[log in to unmask]>
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Learn about the latest and greatest related to complex systems research. 
More at 

The epic battle against coronavirus misinformation and conspiracy theories 

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.

( )

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.

( )

Complex Systems: A Communication Networks Perspective Towards 6G 

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.

( )

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

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