*****  To join INSNA, visit  *****

come to Toronto for the Social Media conference next weekend.
We have great weather -- Now

   Barry Wellman

   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--Walter Cronkite
   Director, NetLab Network      			            FRSC
   Distinguished Visiting Scholar   Social Media Lab   Ryerson University
         Founder, International Network for Social Network Analysis
   NETWORKED: The New Social Operating System  Lee Rainie & Barry Wellman    

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Date: Mon, 15 Jul 2019 11:02:19 +0000
From: "[utf-8] Complexity Digest" <[log in to unmask]>
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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 

Complexity: Science, Engineering or a State of Mind? Towards a Scientific Renaissance 

Is complexity a Science? Is it a possibly useful new way of engineering? In this video narrated by Maxi San Miguel it will be argued that Complexity is a new way of thinking necessary for a scientific renaissance that can transform society.

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Complexity in Medical Informatics

    The topics of the accepted articles include but are not limited to the following: machine and deep learning approaches for health data; data mining and knowledge discovery in healthcare; clinical decision support systems; applications of the genetic algorithm in disease screening, diagnosis, and treatment planning; neurofuzzy system based on genetic algorithm for medical diagnosis and therapy support systems; applications of AI in healthcare; applications of artificial neural networks in medical science; electronic medical record and missing data; network and disease modeling (using administrative data); and health analytics and visualization.

Volume 2019, Article ID 8658124, 2 pages 
Complexity in Medical Informatics
Panagiotis Vlamos, Ilias Kotsireas, and Dimitrios Vlachakis

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Alternative Approaches to Economic Theory: Complexity, Post Keynesian and Ecological Economics. Edited By Victor A. Beker 

The 2007˙˙2008 financial crisis exposed the shortcomings of mainstream economic theory with economists unprepared to deal with it. In the face of this, a major rethinking of economics seems necessary and in presenting alternative approaches to economic theory, this book contributes to the rebuilding of the discipline.

This volume brings together contributions from different perspectives and theoretical approaches that address the challenge of updating the economic theory corpus and seek to recover prestige for this discipline after the failure of neoclassical economics. It addresses a range of topics, including the complexity approach to economics, category theory, the Post-Keynesian approach to micro and macroeconomics, financialisation, multidimensional analysis and ecological economics.

The book is aimed at economics scholars, researchers, academics and practitioners, as well as upper undergraduates and graduates in this area of knowledge. It may also be of interest for people interested in methodological issues in economics and the relationship between economic theory and the real world.

Alternative Approaches to Economic Theory:
Complexity, Post Keynesian and Ecological Economics
Edited By Victor A. Beker

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Element-centric clustering comparison unifies overlaps and hierarchy 

Clustering is one of the most universal approaches for understanding complex data. A pivotal aspect of clustering analysis is quantitatively comparing clusterings; clustering comparison is the basis for many tasks such as clustering evaluation, consensus clustering, and tracking the temporal evolution of clusters. In particular, the extrinsic evaluation of clustering methods requires comparing the uncovered clusterings to planted clusterings or known metadata. Yet, as we demonstrate, existing clustering comparison measures have critical biases which undermine their usefulness, and no measure accommodates both overlapping and hierarchical clusterings. Here we unify the comparison of disjoint, overlapping, and hierarchically structured clusterings by proposing a new element-centric framework: elements are compared based on the relationships induced by the cluster structure, as opposed to the traditional cluster-centric philosophy. We demonstrate that, in contrast to standard clustering
similarity measures, our framework does not suffer from critical biases and naturally provides unique insights into how the clusterings differ. We illustrate the strengths of our framework by revealing new insights into the organization of clusters in two applications: the improved classification of schizophrenia based on the overlapping and hierarchical community structure of fMRI brain networks, and the disentanglement of various social homophily factors in Facebook social networks. The universality of clustering suggests far-reaching impact of our framework throughout all areas of science.

Element-centric clustering comparison unifies overlaps and hierarchy
Alexander J. Gates, Ian B. Wood, William P. Hetrick & Yong-Yeol Ahn
Scientific Reportsvolume 9, Article number: 8574 (2019)

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Special Issue: Information Theory for Human and Social Processes 

Shannon famously applied his ˙˙mathematical theory of communication˙˙ to human communication, alledgedly having his wife, Betty, estimating word probabilities to calcualte the first approximation of the entropy of English. The following decades have seen creative further applications to humans and social processes (e.g., Miller, 1956; Attneave, 1959; Coleman, 1975; Ellis and Fisher, 1975; Cappella, 1979). These efforts lost steam in the 1980s, mainly because of the lack of adequate data, and limited computational power. Both limitations do not apply anymore. The increase in human interactions taking place in digital environments has led to an abundance of behavioral ˙˙big data˙˙, enough even to calculate measures that converge rather slowly.

This Special Issue compiles creative research on the innovative uses of information theory, and its extensions, to better understand human behavior and social processes. Among other topics, the focus is set on human communication, social organization, social algorithms, human˙˙machine interaction, artificial and human intelligence, collaborative teamwork, social media dynamics, information societies, digital development, and cognitive and machine biases˙˙all online and/or offline.

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

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