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SOCNET  December 2015

SOCNET December 2015

Subject:

selected Latest Complexity Digest Posts (fwd)

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Mon, 7 Dec 2015 10:03:43 -0500

Content-Type:

MULTIPART/MIXED

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TEXT/PLAIN (226 lines)

*****  To join INSNA, visit http://www.insna.org  *****


   Barry Wellman
  _______________________________________________________________________
   FRSC                 INSNA Founder               University of Toronto
   http://www.chass.utoronto.ca/~wellman           twitter: @barrywellman
   NETWORKED:The New Social Operating System.  Lee Rainie & Barry Wellman
   MIT Press            http://amzn.to/zXZg39        Print $14  Kindle $9
   _______________________________________________________________________


---------- Forwarded message ----------
Date: Mon, 7 Dec 2015 12:03:24 +0000
From: "[utf-8] Complexity Digest" <[log in to unmask]>
Reply-To: [log in to unmask]
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 http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=0e6adae5c3&e=55e25a0e3e


Measuring online social bubbles

    Social media have become a prevalent channel to access information, spread ideas, and influence opinions. However, it has been suggested that social and algorithmic filtering may cause exposure to less diverse points of view. Here we quantitatively measure this kind of social bias at the collective level by mining a massive datasets of web clicks. Our analysis shows that collectively, people access information from a significantly narrower spectrum of sources through social media and email, compared to a search baseline. The significance of this finding for individual exposure is revealed by investigating the relationship between the diversity of information sources experienced by users at both the collective and individual levels in two datasets where individual users can be analyzed˙˙Twitter posts and search logs. There is a strong correlation between collective and individual diversity, supporting the notion that when we use social media we find ourselves inside ˙˙social
bubbles.˙˙ Our results could lead to a deeper understanding of how technology biases our exposure to new information.

Measuring online social bubbles
Dimitar Nikolov, Diego F.M. Oliveira, Alessandro Flammini, Filippo Menczer

http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=e969e7fae6&e=55e25a0e3e  (http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=cfcc830795&e=55e25a0e3e) ;

See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=b1ce017eb0&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=b94cd3787b&e=55e25a0e3e)



Reputation Effects in Public and Private Interactions

    We study the evolution of cooperation based on reputation. This mechanism is called indirect reciprocity. In a world of binary reputations, people help a good individual but do not help a bad one. They also monitor their own reputation to receive reciprocation from others. We propose a novel model of indirect reciprocity where two types of interactions exist. In a public interaction your behavior is always observed by others. In a private interaction, your behavior is less likely to be observed. We study the competition between honest and hypocritical strategies. The former always help good individuals, whereas the latter do so only in private interactions. We describe conditions for the evolution of honest strategies.

Ohtsuki H, Iwasa Y, Nowak MA (2015) Reputation Effects in Public and Private Interactions. PLoS Comput Biol 11(11): e1004527. http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=2633eded6f&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=c9e84063dd&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=5de5364819&e=55e25a0e3e)



Whom should we sense in ˙˙social sensing˙˙ - analyzing which users work best for social media now-casting

    Given the ever increasing amount of publicly available social media data, there is growing interest in using online data to study and quantify phenomena in the offline ˙˙real˙˙ world. As social media data can be obtained in near real-time and at low cost, it is often used for ˙˙now-casting˙˙ indices such as levels of flu activity or unemployment. The term ˙˙social sensing˙˙ is often used in this context to describe the idea that users act as ˙˙sensors˙˙, publicly reporting their health status or job losses. Sensor activity during a time period is then typically aggregated in a ˙˙one tweet, one vote˙˙ fashion by simply counting. At the same time, researchers readily admit that social media users are not a perfect representation of the actual population. Additionally, users differ in the amount of details of their personal lives that they reveal. Intuitively, it should be possible to improve now-casting by assigning different weights to different user groups.
In this paper, we ask ˙˙How does social sensing actually work?˙˙ or, more precisely, ˙˙Whom should we sense-and whom not-for optimal results?˙˙. We investigate how different sampling strategies affect the performance of now-casting of two common offline indices: flu activity and unemployment rate. We show that now-casting can be improved by (1) applying user filtering techniques and (2) selecting users with complete profiles. We also find that, using the right type of user groups, now-casting performance does not degrade, even when drastically reducing the size of the dataset. More fundamentally, we describe which type of users contribute most to the accuracy by asking if ˙˙babblers are better˙˙. We conclude the paper by providing guidance on how to select better user groups for more accurate now-casting.

Whom should we sense in ˙˙social sensing˙˙ - analyzing which users work best for social media now-casting
Jisun An and Ingmar Weber

EPJ Data Science 2015, 4:22  http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=813c2e4f42&e=55e25a0e3e

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Ultrasociety: How 10, 000 Years of War Made Humans the Greatest Cooperators on Earth: Peter Turchin

    Cooperation is powerful.
There aren˙˙t many highly cooperative species˙˙but they nearly cover the planet. Ants alone account for a quarter of all animal matter. Yet the human capacity to work together leaves every other species standing.
We organize ourselves into communities of hundreds of millions of individuals, inhabit every continent, and send people into space. Human beings are nature˙˙s greatest team players. And the truly astounding thing is, we only started our steep climb to the top of the rankings˙˙overtaking wasps, bees, termites and ants˙˙in the last 10,000 years. Genetic evolution can˙˙t explain this anomaly. Something else is going on. How did we become the ultrasocial animal?
In his latest book, the evolutionary scientist Peter Turchin (War and Peace and War) solves the puzzle using some astonishing results in the new science of Cultural Evolution. The story of humanity, from the first scattered bands of Homo sapiens right through to the greatest empires in history, turns out to be driven by a remorseless logic. Our apparently miraculous powers of cooperation were forged in the fires of war. Only conflict, escalating in scale and severity, can explain the extraordinary shifts in human society˙˙and society is the greatest military technology of all.
Seen through the eyes of Cultural Evolution, human history reveals a strange, paradoxical pattern. Early humans were much more egalitarian than other primates, ruthlessly eliminating any upstart who wanted to become alpha male. But if human nature favors equality, how did the blood-soaked god kings of antiquity ever manage to claim their thrones? And how, over the course of thousands of years, did they vanish from the earth, swept away by a reborn spirit of human equality? Why is the story of human justice a chronicle of millennia-long reversals? Once again, the science points to just one explanation: war created the terrible majesty of kingship, and war obliterated it.
Is endless war, then, our fate? Or might society one day evolve beyond it? There˙˙s only one way to answer that question. Follow Turchin on an epic journey through time, and discover something that generations of historians thought impossible: the hidden laws of history itself.

See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=79401f8d4c&e=55e25a0e3e) , via CxBooks (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=5cd0260295&e=55e25a0e3e)



Complexity and Creative Capacity: Rethinking knowledge transfer, adaptive management and wicked environmental problems (by Kelly Chapman)

    Complexity theories gained prominence in the 1990s with a focus on self-organising and complex adaptive systems. Since then, complexity theory has become one of the fastest growing topics in both the natural and social sciences, and touted as a revolutionary way of understanding the behaviour of complex systems.

This book uses complexity theory to surface and challenge the deeply held cultural assumptions that shape how we think about reality and knowledge. In doing so it shows how our traditional approaches to generating and applying knowledge may be paradoxically exacerbating some of the ˙˙wicked˙˙ environmental problems we are currently facing. The author proposes an innovative and compelling argument for rejecting old constructs of knowledge transfer, adaptive management and adaptive capacity. The book also presents a distinctively coherent and comprehensive synthesis of cognition, learning, knowledge and organizing from a complexity perspective. It concludes with a reconceptualization of the problem of knowledge transfer from a complexity perspective, proposing the concept of creative capacity as an alternative to adaptive capacity as a measure of resilience in socio-ecological systems.

Although written from an environmental management perspective, it is relevant to the broader natural sciences and to a range of other disciplines, including knowledge management, organizational learning, organizational management, and the philosophy of science.



See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=51190d371b&e=55e25a0e3e) , via CxBooks (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=56ca388e74&e=55e25a0e3e)



Complex Systems Science: Where Does It Come From and Where is It Going To?

    Today complex systems science is rapidly growing as a discipline, with relevance to many areas of science and as an approach to addressing a wide range of real world problems. Understanding the fundamental mathematical origins of complex systems science reveals its conceptual richness and ability to advance science and expand its application. I will review these origins, describe some current applications, and point to the opportunities of the future.

Complex Systems Science: Where Does It Come From and Where is It Going To?
Yaneer Bar-Yam

Opening plenary address at the Conference on Complex Systems 2015, at Arizona State University in Tempe, Arizona.

http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=65e1d76093&e=55e25a0e3e
Complexity Digest's insight:

See Also: Videos of all plenary talks at

See it on Scoop.it (http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=6053f5cc8e&e=55e25a0e3e) , via Talks (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=b4087918af&e=55e25a0e3e)


Eigencentrality based on dissimilarity measures reveals central nodes in complex networks

    One of the most important problems in complex network˙˙s theory is the location of the entities that are essential or have a main role within the network. For this purpose, the use of dissimilarity measures (specific to theory of classification and data mining) to enrich the centrality measures in complex networks is proposed. The centrality method used is the eigencentrality which is based on the heuristic that the centrality of a node depends on how central are the nodes in the immediate neighbourhood (like rich get richer phenomenon). This can be described by an eigenvalues problem, however the information of the neighbourhood and the connections between neighbours is not taken in account, neglecting their relevance when is one evaluates the centrality/importance/influence of a node. The contribution calculated by the dissimilarity measure is parameter independent, making the proposed method is also parameter independent. Finally, we perform a comparative study of our
method versus other methods reported in the literature, obtaining more accurate and less expensive computational results in most cases.

Eigencentrality based on dissimilarity measures reveals central nodes in complex networks
A. J. Alvarez-Socorro, G. C. Herrera-Almarza & L. A. González-Díaz

Scientific Reports 5, Article number: 17095 (2015)
http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=8ddeb53e84&e=55e25a0e3e  (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=b55dc25943&e=55e25a0e3e) ;

See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=ed3e9d14a1&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=f9909e06e7&e=55e25a0e3e)



The World the Game Theorists Made (by Paul Erickson)

    In recent decades game theory˙˙the mathematics of rational decision-making by interacting individuals˙˙has assumed a central place in our understanding of capitalist markets, the evolution of social behavior in animals, and even the ethics of altruism and fairness in human beings. With game theory˙˙s ubiquity, however, has come a great deal of misunderstanding. Critics of the contemporary social sciences view it as part of an unwelcome trend toward the marginalization of historicist and interpretive styles of inquiry, and many accuse its proponents of presenting a thin and empirically dubious view of human choice.

The World the Game Theorists Made seeks to explain the ascendency of game theory, focusing on the poorly understood period between the publication of John von Neumann and Oscar Morgenstern˙˙s seminal Theory of Games and Economic Behavior in 1944 and the theory˙˙s revival in economics in the 1980s. Drawing on a diverse collection of institutional archives, personal correspondence and papers, and interviews, Paul Erickson shows how game theory offered social scientists, biologists, military strategists, and others a common, flexible language that could facilitate wide-ranging thought and debate on some of the most critical issues of the day.



See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=63888ba9f4&e=55e25a0e3e) , via CxBooks (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=ca67af4db5&e=55e25a0e3e)



Age of System: Understanding the Development of Modern Social Science (by Hunter Heyck)

    Before the Second World War, social scientists struggled to define and defend their disciplines. After the war, "high modern" social scientists harnessed new resources in a quest to create a unified understanding of human behavior˙˙and to remake the world in the image of their new model man.

In Age of System, Hunter Heyck explains why social scientists˙˙shaped by encounters with the ongoing "organizational revolution" and its revolutionary technologies of communication and control˙˙embraced a new and extremely influential perspective on science and nature, one that conceived of all things in terms of system, structure, function, organization, and process. He also explores how this emerging unified theory of human behavior implied a troubling similarity between humans and machines, with freighted implications for individual liberty and self-direction.

These social scientists trained a generation of decision-makers in schools of business and public administration, wrote the basic textbooks from which millions learned how the economy, society, polity, culture, and even the mind worked, and drafted the position papers, books, and articles that helped set the terms of public discourse in a new era of mass media, think tanks, and issue networks. Drawing on close readings of key texts and a broad survey of more than 1,800 journal articles, Heyck follows the dollars˙˙and the dreams˙˙of a generation of scholars that believed in "the system." He maps the broad landscape of changes in the social sciences, focusing especially intently on the ideas and practices associated with modernization theory, rational choice theory, and modeling. A highly accomplished historian, Heyck relays this complicated story with unusual clarity.



See it on Scoop.it (http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=7f8057c407&e=55e25a0e3e) , via CxBooks (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=4c172b6123&e=55e25a0e3e)


Democracy-Growth Dynamics for Richer and Poorer Countries

    We study the empirical relationship between democracy and growth using grid-based panel regression and regime-transition frameworks. Our set-up nests several existing approaches, such as Barro (1996) and Gerring et al. (2005), and reconciles their conflicting messages in a more general model, and we identify the best-fitting discounts and memories. Our main finding is that democracy --best-modelled as a stock variable-- does cause growth, especially beyond the immediate short-run, by enabling the accumulation of physical, human, social and political capitals. Beyond threshold levels of democratic and economic development, however, there are incentives for de-democratization in order to boost short-run growth at the cost of higher sustained long-run growth.

Democracy-Growth Dynamics for Richer and Poorer Countries

Heinrich H. Nax, Anke B Schorr

http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=c8fc3a1660&e=55e25a0e3e

See it on Scoop.it (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=8f4a73e48f&e=55e25a0e3e) , via Papers (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=ab5a0bb205&e=55e25a0e3e)



The 2016 Conference on Complexity Systems

    The Conference on Complex Systems (CCS) has become a major venue for the Complex Systems Community since they were started in 2003. After a successful event in the USA in 2015 we are now back in Europe. In AMSTERDAM(!).  CCS˙˙16 will be a major international conference and event in the area of complex systems and interdisciplinary science in general.

The 2016 Conference on Complexity Systems

Amsterdam, The Netherlands.

2016-09-19:23

http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=14b40ed0b4&e=55e25a0e3e (http://unam.us4.list-manage2.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=c666e9d56d&e=55e25a0e3e)

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NTU 2016 Winter School

    What is complexity science? What are complex systems? And why do physicists like Stephen Hawking and Heinz Pagels think complexity science will be a dominant force, not only in shaping our pursuit of scientific truth, but also in changing how we think about societies, and our place in them?

The 2016 Winter School provides an overview of complexity and complex systems science that empowers participants search for their own answers to these questions. The knowledge gained will enable participants to apply complexity science ideas in their own domains.

Essentially, the school will:

˙˙ Teach basic aspects of complexity and complex systems, answering the question: What makes a system complex? Aspects that will be covered include nonlinearity, order disorder & chaos, emergence and complex adaptive systems

˙˙ Introduce methods, models and simulation tools to study the behaviours of complex systems and provide hands-on experience on through the use of software for building, simulating and visualizing complex networks. Participants are encouraged to bring their own data, work in groups mentored by instructors. Participants will then have the opportunity to present their own findings at the end of the week long course.
˙˙ Provide insights into how complexity manifests itself in real life e.g. politics & governance, eco-systems, cities and spreading phenomena such as rumours, epidemics, economics and innovation.

NTU Winter School 2016

March, 2016

http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=5afed26316&e=55e25a0e3e

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Quantum Walks with Gremlin

    A quantum walk places a traverser into a superposition of both graph location and traversal "spin." The walk is defined by an initial condition, an evolution determined by a unitary coin/shift-operator, and a measurement based on the sampling of the probability distribution generated from the quantum wavefunction. Simple quantum walks are studied analytically, but for large graph structures with complex topologies, numerical solutions are typically required. For the quantum theorist, the Gremlin graph traversal machine and language can be used for the numerical analysis of quantum walks on such structures. Additionally, for the graph theorist, the adoption of quantum walk principles can transform what are currently side-effect laden traversals into pure, stateless functional flows. This is true even when the constraints of quantum mechanics are not fully respected (e.g. reversible and unitary evolution). In sum, Gremlin allows both types of theorist to leverage each other's
constructs for the advancement of their respective disciplines.

Quantum Walks with Gremlin
Marko A. Rodriguez, Jennifer H. Watkins

http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=dea24b3ea9&e=55e25a0e3e
Complexity Digest's insight:

See Also http://unam.us4.list-manage1.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=a8abe5e50e&e=55e25a0e3e (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=3bdbab19db&e=55e25a0e3e)

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

You can contribute to Complexity Digest selecting one of our topics (http://unam.us4.list-manage.com/track/click?u=0eb0ac9b4e8565f2967a8304b&id=9c2a29e35a&e=55e25a0e3e ) and using the "Suggest" button.
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