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   Barry Wellman

                      Faculty of Information (iSchool)
   University of Toronto                          Toronto Canada M5S 3G6          twitter: @barrywellman
   NETWORKED:The New Social Operating System. Lee Rainie & Barry Wellman
   MIT Press        Print $15  Kindle $9

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Date: Mon, 21 Jul 2014 09:59:17 -0500
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Subject: [comdig] Latest Complexity Digest Posts

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

The future lies in uncertainty

    Statisticians have celebrated a lot recently. 2013 marked the 300th anniversary of Jacob Bernoulli's Ars Conjectandi, which used probability theory to explore the properties of statistics as more observations were taken. It was also the 250th anniversary of Thomas Bayes' essay on how humans can sequentially learn from experience, steadily updating their beliefs as more data become available (1). And it was the International Year of Statistics (2). Now that the bunting has been taken down, it is a good time to take stock of recent developments in statistical science and examine its role in the age of Big Data.
Much enthusiasm for statistics hangs on the ever-increasing availability of large data sets, particularly when something has to be ranked or classified. These situations arise, for example, when deciding which book to recommend, working out where your arm is when practicing golf swings in front of a games console, or (if you're a security agency) deciding whose private e-mail to read first. Purely data-based approaches, under the title of machine-learning, have been highly successful in speech recognition, real-time interpretation of moving images, and online translation.

The future lies in uncertainty
. D. J. Spiegelhalter

Science 18 July 2014:
Vol. 345 no. 6194 pp. 264-265
Complexity Digest's insight:

  Predicting the past is very easy. Predicting the future is not so easy   -Ignacio MÚndez

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Friendship and natural selection

    More than any other species, humans form social ties to individuals who are neither kin nor mates, and these ties tend to be with similar people. Here, we show that this similarity extends to genotypes. Across the whole genome, friends   genotypes at the single nucleotide polymorphism level tend to be positively correlated (homophilic). In fact, the increase in similarity relative to strangers is at the level of fourth cousins. However, certain genotypes are also negatively correlated (heterophilic) in friends. And the degree of correlation in genotypes can be used to create a   friendship score   that predicts the existence of friendship ties in a hold-out sample. A focused gene-set analysis indicates that some of the overall correlation in genotypes can be explained by specific systems; for example, an olfactory gene set is homophilic and an immune system gene set is heterophilic, suggesting that these systems may play a role in the formation or maintenance of friendship ties.
Friends may be a kind of   functional kin.   Finally, homophilic genotypes exhibit significantly higher measures of positive selection, suggesting that, on average, they may yield a synergistic fitness advantage that has been helping to drive recent human evolution.

Friendship and natural selection
Nicholas A. Christakis and James H. Fowler


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How collective comparisons emerge without individual comparisons of the options

    Collective decisions in animal groups emerge from the actions of individuals who are unlikely to have global information. Comparative assessment of options can be valuable in decision-making. Ant colonies are excellent collective decision-makers, for example when selecting a new nest-site.

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Coaction versus reciprocity in continuous-time models of cooperation

    Cooperating animals frequently show closely coordinated behaviours organized by a continuous flow of information between interacting partners. Such real-time coaction is not captured by the iterated prisoner  s dilemma and other discrete-time reciprocal cooperation games, which inherently feature a delay in information exchange. Here, we study the evolution of cooperation when individuals can dynamically respond to each other  s actions.

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  What Is the Teacher Trying to Teach Students if They Are All Busy Constructing Their Own Private Worlds?  : Introduction to the Special Issue

    Context: Ernst von Glasersfeld introduced radical constructivism in 1974 as a new interpretation of Jean Piaget  s constructivism to give new meanings to the notions of knowledge, communication, and reality. He also claimed that RC would affect traditional theories of education. Problem: After 40 years it has become necessary to review and evaluate von Glasersfeld  s claim. Also, has RC been successful in taking the   social turn   in educational research, or is it unable to go beyond   private worlds? Method: We provide an overview of contributed articles that were written with the aim of showing whether RC has an impact on educational research, and we discuss three core issues: Can RC account for inter-individual aspects? Is RC a theory of learning? And should Piaget be regarded as a radical constructivist? Results: We argue that the contributed papers demonstrate the efficiency of the application of RC to educational research and practice. Our argumentation also shows that in
RC it would be misleading to claim a dichotomy between cognition and social interaction (rather, social constructivism is a radical constructivism), that RC does not contain a theory of mathematics learning any more or less than it contains a theory of mathematics teaching, and that Piaget should not be considered a mere trivial constructivist. Implications: Still one of the most challenging influences on educational research and practice, RC is ready to embark on many further questions, including its relationship with other constructivist paradigms, and to make progress in the social dimension.

Riegler A. & Steffe L. P. (2014)   What Is the Teacher Trying to Teach Students if They Are All Busy Constructing Their Own Private Worlds?  : Introduction to the Special Issue. Constructivist Foundations 9(3): 297  301. Available at

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    The NetSci-X is the first Network Science Conference outside the USA-Europe axis. It will bring together leading researchers and practitioners working in the emerging area of network science.
The conference fosters interdisciplinary communication and collaboration, with focus on novel directions in network research within the biological and environmental sciences, computer and information sciences, social sciences, finance and business, among others.
The NetSci-X Conference will be held in January 2015 in Rio de Janeiro, Brazil, at the Getulio Vargas Foundation  one of the main Think Tanks in the world and leading educational and research institution in Brazil.

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Seventh International Workshop on Guided Self-Organization

    The workshop will bring together researchers from a richly diverse background who share interest in understanding and designing self-organising systems. Of particular interest are well-founded, but general methods for characterizing such systems in a principled way with the view of ultimately allowing them to be guided toward prespecified goals. Information theory, nonlinear dynamics and graph theory are core to many of these methods, and quantifying complexity and its sources is a common theme.

This year, the workshop is organised in collaboration with the BrainLinks-BrainTools cluster of excellence at University of Freiburg ( ), and one focus theme will be guided self-organisation in neural systems.

Seventh International Workshop on Guided Self-Organisation (GSO-2014) to be held from December 16-18, 2014 in Freiburg, Germany.

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Early Warning Signs in Social-Ecological Networks

    A number of social-ecological systems exhibit complex behavior associated with nonlinearities, bifurcations, and interaction with stochastic drivers. These systems are often prone to abrupt and unexpected instabilities and state shifts that emerge as a discontinuous response to gradual changes in environmental drivers. Predicting such behaviors is crucial to the prevention of or preparation for unwanted regime shifts. Recent research in ecology has investigated early warning signs that anticipate the divergence of univariate ecosystem dynamics from a stable attractor. To date, leading indicators of instability in systems with multiple interacting components have remained poorly investigated. This is a major limitation in the understanding of the dynamics of complex social-ecological networks. Here, we develop a theoretical framework to demonstrate that rising variance  measured, for example, by the maximum element of the covariance matrix of the network  is an effective leading
indicator of network instability. We show that its reliability and robustness depend more on the sign of the interactions within the network than the network structure or noise intensity. Mutualistic, scale free and small world networks are less stable than their antagonistic or random counterparts but their instability is more reliably predicted by this leading indicator. These results provide new advances in multidimensional early warning analysis and offer a framework to evaluate the resilience of social-ecological networks.

Early Warning Signs in Social-Ecological Networks.

PLoS ONE 9(7): e101851. doi:10.1371/journal.pone.0101851 (2014)

Suweis Samir, D'Odorico Paolo

Code of the analysis available at

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Complexity: A Very Short Introduction (by John H. Holland)

    The importance of complexity is well-captured by Hawking's comment: "Complexity is the science of the 21st century". From the movement of flocks of birds to the Internet, environmental sustainability, and market regulation, the study and understanding of complex non-linear systems has become highly influential over the last 30 years.

In this Very Short Introduction, one of the leading figures in the field, John Holland, introduces the key elements and conceptual framework of complexity. From complex physical systems such as fluid flow and the difficulties of predicting weather, to complex adaptive systems such as the highly diverse and interdependent ecosystems of rainforests, he combines simple, well-known examples -- Adam Smith's pin factory, Darwin's comet orchid, and Simon's 'watchmaker' -- with an account of
the approaches, involving agents and urn models, taken by complexity theory.

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Complexity in Economics: Cutting Edge Research (edited by Marisa Faggini & Anna Parziale)

    In this book, leading experts discuss innovative components of complexity theory and chaos theory in economics.

The underlying perspective is that investigations of economic phenomena should view these phenomena not as deterministic, predictable and mechanistic but rather as process dependent, organic and always evolving.

The aim is to highlight the exciting potential of this approach in economics and its ability to overcome the limitations of past research and offer important new insights. The book offers a stimulating mix of theory, examples and policy.

By casting light on a variety of topics in the field, it will provide an ideal platform for researchers wishing to deepen their understanding and identify areas for further investigation.

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Complexity Science and World Affairs (by Walter C. Clemens Jr.)

    Applies complexity science to the study of international politics. Why did some countries transition peacefully from communist rule to political freedom and market economies, while others did not? Why did the United States enjoy a brief moment as the sole remaining superpower, and then lose power and influence across the board? What are the prospects for China, the main challenger to American hegemony? In Complexity Science and World Affairs, Walter C. Clemens Jr. demonstrates how the basic concepts of complexity science can broaden and deepen the insights gained by other approaches to the study of world affairs. He argues that societal fitness  the ability of a social system to cope with complex challenges and opportunities  hinges heavily on the values and way of life of each society, and serves to explain why some societies gain and others lose. Applying theory to several rich case studies, including political developments across post  Soviet Eurasia and the United States,
Clemens shows that complexity science offers a powerful set of tools for advancing the study of international relations, comparative government, and, more broadly, the social sciences.

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