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winter has come to Toronto. MSM seems surprised.
We just cocoon and write stuff
Selected abstracts below
   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--You Are There!
   Director, NetLab Network      			            FRSC
         Founder, International Network for Social Network Analysis
   NETWORKED: The New Social Operating System  Lee Rainie & Barry Wellman    

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Date: Mon, 20 Jan 2020 12:03:07 +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 

Tenth International Conference on Complex Systems 

The International Conference on Complex Systems is a unique interdisciplinary forum that unifies and bridges the traditional domains of science and a multitude of real world systems. Participants will contribute and be exposed to mind expanding concepts and methods from across the diverse field of complex systems science. The conference will be held July 26-31, 2020, in Nashua, NH, USA.

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W. Brian Arthur (Part 1) on The History of Complexity Economics 

From its beginnings as a discipline nearly 150 years ago, economics rested on assumptions that don˙˙t hold up when studied in the present day. The notion that our economic systems are in equilibrium, that they˙˙re made of actors making simple rational and self-interested decisions with perfect knowledge of society˙˙ these ideas prove about as useful in the Information Age as Newton˙˙s laws of motion are to quantum physicists. A novel paradigm for economics, borrowing insights from ecology and evolutionary biology, started to emerge at SFI in the late 1980s ˙˙ one that treats our markets and technologies as systems out of balance, serving metabolic forces, made of agents with imperfect information and acting on fundamental uncertainty. This new complexity economics uses new tools and data sets to shed light on puzzles standard economics couldn˙˙t answer ˙˙ like why the economy grows, how sudden and cascading crashes happen, why some companies and cities lock in permanent competitive advantages, and
how technology evolves. And complexity economics offers insights back to biology, providing a new lens through which to understand the vastly intricate exchanges on which human life depends.
This week˙˙s guest is W. Brian Arthur, External Professor at the Santa Fe Institute, Fellow at the Center for Advanced Study in the Behavioral Sciences at Stanford, and Visiting Researcher at Xerox PARC. In this first part of a two-episode conversation, we discuss the heady early days when complex systems science took on economics, and how biology provided a new paradigm for understanding our financial and technological systems. Tune in next week for part two...

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Postdoctoral Fellows in The Center for Social and Biomedical Complexity Indiana University Bloomington, Luddy School of Informatics, Computing, and Engineering

    The Center for Social and Biomedical Complexity (CSBC: ) at Indiana University Bloomington is accepting applications for one or more full-time non-tenure track postdoctoral fellows to conduct interdisciplinary research in Complex Networks and Systems applied to various social, ecological, biological, medicine and health problems. The expected start date for the appointments is February 2020. Candidates interested in conducting research in urban community-environment systems, or network science methods to analyze and visualize information relevant for epilepsy and other chronic diseases are encouraged to apply. The appointments are full-time for 12 months, with potential to be extended an additional year subject to funding and satisfactory performance. We offer a competitive salary with generous benefits. The postdocs will join a dynamic and interdisciplinary team that includes systems scientists, biologists, computer scientists, and social scientists. The
postdocs will work with Prof. Luis M Rocha ( ) and Prof. Johan Bollen ( ).

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Decentralization in Digital Societies ˙˙ A Design Paradox

    Evangelos Pournaras

Digital societies come with a design paradox: On the one hand, technologies, such as Internet of Things, pervasive and ubiquitous systems, allow a distributed local intelligence in interconnected devices of our everyday life such as smart phones, smart thermostats, self-driving cars, etc. On the other hand, Big Data collection and storage is managed in a highly centralized fashion, resulting in privacy-intrusion, surveillance actions, discriminatory and segregation social phenomena. What is the difference between a distributed and a decentralized system design? How "decentralized" is the processing of our data nowadays? Does centralized design undermine autonomy? Can the level of decentralization in the implemented technologies influence ethical and social dimensions, such as social justice? Can decentralization convey sustainability? Are there parallelisms between the decentralization of digital technology and the decentralization of urban development?

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Efficient sentinel surveillance strategies for preventing epidemics on networks 

Ewan Colman, Petter Holme, Hiroki Sayama, Carlos Gershenson

Surveillance plays a crucial role in preventing emerging infectious diseases from becoming epidemic. In circumstances where it is possible to monitor the infection status of certain people, transport hubs, or hospitals, early detection of the disease allows interventions to be implemented before most of the damage can occur, or at least its impact can be mitigated. This paper addresses the question of which nodes we should select in a network of individuals susceptible to some infectious disease in order to minimize the number of casualties. By simulating disease outbreaks on a collection of empirical and synthetic networks we show that the best strategy depends on topological characteristics of the network. For highly modular or spatially embedded networks it is better to place the sentinels on nodes distributed across different regions. However, if the degree heterogeneity is high, then a strategy that targets network hubs is preferred. We further consider the consequences of having an
incomplete sample of the network and demonstrate that the value of new information diminishes as more data is collected. Finally we find further marginal improvements using two heuristics informed by known results in graph theory that exploit the fragmented structure of sparse network data.

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

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