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I actually watched 4 football games this weekend. (That's US-style 

   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
   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, 14 Jan 2019 12:04:48 +0000
From: "[utf-8] Complexity Digest" <[log in to unmask]>
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Subject: [utf-8] Latest Complexity Digest Posts

Learn about the latest and greatest related to complex systems research. More at

Opinion Dynamics and Collective Decisions

    We expect that democracy enables us to utilize collective intelligence such that our collective decisions build and enhance social welfare, and such that we accept their distributive and normative consequences. Collective decisions are produced by voting procedures which aggregate individual preferences and judgments. Before and after, individual preferences and judgments change as their underlying attitudes, values, and opinions change through discussion and deliberation. In large groups, these dynamics naturally go beyond the scope of the individual and consequently might show unexpected self-driven macroscopic systems dynamics following socio-physical laws. On the other hand, aggregated information and preferences as communicated through media, polls, political parties, or interest groups, also play a large role in the individual opinion formation process. Further on, actors are also capable of strategic opinion formation in the light of a pending referendum, election or
other collective decision. Opinion dynamics and collective decision should thus not only be tackled by social choice, game theory, political and social psychology, but also from a systems dynamics and sociophysics perspective.

Advances in Complex SystemsVol. 21, No. 06n07, 1802002 (2018) Full Access

Source: (

Taking census of physics

Over the past decades, the diversity of areas explored by physicists has exploded, encompassing new topics from biophysics and chemical physics to network science. However, it is unclear how these new subfields emerged from the traditional subject areas and how physicists explore them. To map out the evolution of physics subfields, here, we take an intellectual census of physics by studying physicists˙˙ careers. We use a large-scale publication data set, identify the subfields of 135,877 physicists and quantify their heterogeneous birth, growth and migration patterns among research areas. We find that the majority of physicists began their careers in only three subfields, branching out to other areas at later career stages, with different rates and transition times. Furthermore, we analyse the productivity, impact and team sizes across different subfields, finding drastic changes attributable to the recent rise in large-scale collaborations. This detailed, longitudinal census
of physics can inform resource allocation policies and provide students, editors and scientists with a broader view of the field˙˙s internal dynamics.

Taking census of physics
Federico Battiston, Federico Musciotto, Dashun Wang, Albert-László Barabási, Michael Szell & Roberta Sinatra
Nature Reviews Physics volume 1, pages89˙˙97 (2019)

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Pull out all the stops: Textual analysis via punctuation sequences

    Whether enjoying the lucid prose of a favorite author or slogging through some other writer's cumbersome, heavy-set prattle (full of parentheses, em-dashes, compound adjectives, and Oxford commas), readers will notice stylistic signatures not only in word choice and grammar, but also in punctuation itself. Indeed, visual sequences of punctuation from different authors produce marvelously different (and visually striking) sequences. Punctuation is a largely overlooked stylistic feature in ``stylometry'', the quantitative analysis of written text. In this paper, we examine punctuation sequences in a corpus of literary documents and ask the following questions: Are the properties of such sequences a distinctive feature of different authors? Is it possible to distinguish literary genres based on their punctuation sequences? Do the punctuation styles of authors evolve over time? Are we on to something interesting in trying to do stylometry without words, or are we full of sound
and fury (signifying nothing)?

Pull out all the stops: Textual analysis via punctuation sequences
Alexandra N. M. Darmon Marya Bazzi Sam D. Howison Mason Porter

Source: (

Complexity and Self-Organization | Frontiers Research Topic

Complexity occurs when relevant interactions prevent the study of elements of a system in isolation. These interactions between elements may lead to the self-organization of the system. In computational intelligence, complexity and self-organization have been studied and exploited with different purposes. This Research Topic aims to bring together novel research into a coherent collection, spanning from theory and methods to simulations and applications.

Computational measures of complexity and self-organization have been proposed and applied to study a broad range of phenomena. Methodologies for facing complexity and harnessing self-organization have been used to design and build a variety of systems. Computer simulations have been tools which enabled us to study complexity and self-organization, from cellular automata and artificial neural networks to multi-agent systems and computational social science. The applications of these approaches have been vast.

Considering that complexity and self-organization are very broad themes, this Research Topic focusses only on the aspects related to computational intelligence.

Submission Deadlines
31 July 2019 Abstract
30 September 2019 Manuscript

Source: (

Complex Systems Summer School | Santa Fe Institute

The SFI Complex Systems Summer School (CSSS) offers an intensive 4-week introduction to complex behavior in mathematical, physical, living, and social systems. Lectures are taught by the faculty of the Santa Fe Institute (SFI) and other leading educators and scholars. The school is for graduate students, postdoctoral fellows, and professionals seeking to transcend traditional disciplinary boundaries, take intellectual risks, and ask big questions about complex systems.

The program consists of an intensive series of lectures, labs, and discussions focusing on foundational concepts, tools, and current topics in complexity science. These include nonlinear dynamics, scaling theory, information theory, adaptation and evolution, networks, machine learning, agent-based models, and other topical areas and case studies. Participants collaborate in developing novel research projects throughout the four weeks of the program that culminate in final presentations and papers.

Begins: Jun 09 2019
Ends: Jul 05 2019

Deadline extension: now Thursday, January 31.

Source: (

Causal deconvolution by algorithmic generative models

New paper in Nature Machine Intelligence and a video produced by Nature shows how small programs can help deconvolve signals and data: and

"Most machine learning approaches extract statistical features from data, rather than the underlying causal mechanisms. A different approach analyses information in a general way by extracting recursive patterns from data using generative models under the paradigm of computability and algorithmic information theory.

Complex behaviour emerges from interactions between objects produced by different generating mechanisms. Yet to decode their causal origin(s) from observations remains one of the most fundamental challenges in science. This paper introduces a universal, unsupervised and parameter-free model-oriented approach, based on the seminal concept and the first principles of algorithmic probability, to decompose an observation into its most likely algorithmic generative models."

Source: (

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

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