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Non-Equilibrium Social Science
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Modelling social networks reveals how information spreads

Modelling social networks reveals how information spreads | Non-Equilibrium Social Science | Scoop.it
The way information spreads through society has changed significantly over the past decade with the advent of online social networking.

 

In the context of history, connectors are among the people who are pioneers of social change. We need only look back at political change within global society today to find examples of connectors that played a significant role in affecting that change at the time.

Experiments of this type (perhaps on a larger scale) could help develop our understanding of how our society functions in the 21st century. The speed at which information can spread, and the fidelity of the spread of that information, is important to perhaps all aspects of society. 


Via Marc Tirel, Shaolin Tan
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Marc Tirel's curator insight, October 14, 2013 4:25 AM

Interesting experimentation and conclusion : 

Experiments of this type (perhaps on a larger scale) could help develop our understanding of how our society functions in the 21st century. The speed at which information can spread, and the fidelity of the spread of that information, is important to perhaps all aspects of society.

Shaolin Tan's curator insight, October 14, 2013 8:59 PM

In the experiment, if individuals are allowed to change to color accroding to the neighborhood, it may be more interesting. I think the evolutionary game dynamics on complex provides a proper model to characterize the above diffusion process.

António F Fonseca's curator insight, December 28, 2013 7:12 AM

First principles in information difusion on networks.

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The Simple Rules of Social Contagion

It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is significantly more complex than the prediction of the pathogen model. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of the exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We apply our model to real-time forecasting of user behavior.

 

The Simple Rules of Social Contagion
Nathan O. Hodas, Kristina Lerman

http://arxiv.org/abs/1308.5015


Via Complexity Digest, Marinella De Simone, António F Fonseca
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António F Fonseca's curator insight, December 23, 2013 7:12 AM

Another paper about information propagation. A study on the user interface of two social sites, mainly the problem of limited attention and attention managment.

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Brain-Style Chips Will Make Smartphones Truly Smart

Brain-Style Chips Will Make Smartphones Truly Smart | Non-Equilibrium Social Science | Scoop.it

We should look to biology to figure out how to make smartphones more ­helpful, says M. Anthony Lewis.

 

A modern smartphone is the most powerful information portal the world has known, integrating a traditional telephone with a powerful Internet-connected computer capable of navigating, playing multimedia, and taking photos. I think the next major step in smartphone evolution is obvious: the devices will become intelligent assistants that can perceive the environment and follow our commands. This will become possible thanks to progress in building chips inspired by the functioning of mammalian brains

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International Symposium on Distributed Computing and Artificial Intelligence - Special session on Multi-Agents Macroeconomics

International Symposium on Distributed Computing and Artificial Intelligence - Special session on Multi-Agents Macroeconomics | Non-Equilibrium Social Science | Scoop.it

10th International Symposium on Distributed Computing and Artificial Intelligence, 22nd-25th May, 2013, Salamanca (Spain).

 

The special session on Multi-Agents Macroeconomics is an international forum which aims at sharing ideas, projects, researches results, models and experiences associated with the building of computational macroeconomic models. The special session will be held in Salamanca (Spain) as the part of the 11st International Symposium Distributed Computing and Artificial Intelligence 2014.

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Rescooped by NESS from Complexity - Complex Systems Theory
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BBC Radio 4 - In Our Time, Complexity

BBC Radio 4 - In Our Time, Complexity | Non-Equilibrium Social Science | Scoop.it

Melvyn Bragg and his guests discuss complexity and how it can help us understand the world around us. When living beings come together and act in a group, they do so in complicated and unpredictable ways: societies often behave very differently from the individuals within them. Complexity was a phenomenon little understood a generation ago, but research into complex systems now has important applications in many different fields, from biology to political science. Today it is being used to explain how birds flock, to predict traffic flow in cities and to study the spread of diseases.


Via Bernard Ryefield
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ComplexInsight's curator insight, January 12, 1:43 AM

You know a topic or meme has migrated into cultural hype-scape when Melvyn Bragg discusses it on Radio 4. However it's good to see complex adaptive systems research getting  considered coverage outside of the likes of Scientific American and New Scientist who have long promoted balanced views of the field.

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SKIN 3 Workshop: Joining Complexity Science and Social Simulation for Policy

SKIN 3 Workshop: Joining Complexity Science and Social Simulation for Policy | Non-Equilibrium Social Science | Scoop.it

This 2-days workshop organised by the EA European Academy of Technology and Innovation Assessment GmbHas its annual conference with two co-organisers and one local host will bring together two scientific communities to join forces in research on innovation policy modelling. Innovation intersects the concerns of complexity science and social simulation. The intention of the workshop is to explore how complexity models and social simulation can be used to improve and inform the innovation policy making process. The workshop will take place at Eotvos University, Budapest (Hungary), from 22 to 23 May 2014 and is supported by the EGovPoliNet project.

The workshop will focus on three key overlapping themes:

Modelling, understanding and managing innovation policy using the SKIN modelLarge scale data and scalability for research and innovation policy modellingSKIN between complexity science and social science: mechanisms and components
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Rescooped by NESS from Philosophy and Complexity
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From Beyond the Coming Age of Networked Matter, by Bruce Sterling

From Beyond the Coming Age of Networked Matter, by Bruce Sterling | Non-Equilibrium Social Science | Scoop.it

Over the next few decades, a confluence of breakthroughs in physics, engineering, biology, computation, and complexity science will give us new lenses to observe the wondrous interconnections surrounding us and within us. In the future we’re moving toward, we won’t only observe complex systems, we’ll also modify and even create them in vivo and with purpose. It will be an era of huge possibility, daunting pitfalls, and high weirdness.

To help make this future tangible, we commissioned some of our favorite writers of speculative fiction -- Cory Doctorow, Rudy Rucker, Ramez Naam, Bruce Sterling, Madeline Ashby, and Warren Ellis -- to write short stories tied to our research theme. The anthology, titled An Aura of Familiarity: Visions from the Coming Age of Networked Matter, contains six stories all released under a Creative Commons license. The accompanying art is by Daniel Martin Diaz.


Via Mariusz Leś, John Symons
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António F Fonseca's curator insight, December 18, 2013 12:22 PM

Funny story about the network mania of our days.

Rescooped by NESS from Complexity - Complex Systems Theory
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How far should we trust scientific models? – Jon Turney – Aeon

How far should we trust scientific models? – Jon Turney – Aeon | Non-Equilibrium Social Science | Scoop.it
In economics, climate science and public health, computer models help us decide how to act. But can we trust them?

Via Bernard Ryefield
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luiy's curator insight, December 17, 2013 4:23 AM

Here’s a simple recipe for doing science. Find a plausible theory for how some bits of the world behave, make predictions, test them experimentally. If the results fit the predictions, then the theory might describe what’s really going on. If not, you need to think again. Scientific work is vastly diverse and full of fascinating complexities. Still, the recipe captures crucial features of how most of it has been done for the past few hundred years.

 

Now, however, there is a new ingredient. Computer simulation, only a few decades old, is transforming scientific projects as mind-bending as plotting the evolution of the cosmos, and as mundane as predicting traffic snarl-ups. What should we make of this scientific nouvelle cuisine? While it is related to experiment, all the action is in silico — not in the world, or even the lab. It might involve theory, transformed into equations, then computer code. Or it might just incorporate some rough approximations, which are good enough to get by with. Made digestible, the results affect us all.

Rescooped by NESS from Complex Systems Digital Campus
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Complicity: An International Journal of Complexity and Education

Complicity: An International Journal of Complexity and Education | Non-Equilibrium Social Science | Scoop.it

Complicity is an open access (free to all readers), peer-reviewed journal that publishes original articles on all aspects of education that are informed by the idea of complexity (in its technical, applied, philosophical, theoretical, or narrative manifestations). The journal strives to serve as a forum for both theoretical and practical contributions and to facilitate the exchange of diverse ideas and points of view related to complexity in education.


Via Complex Systems Digital Campus
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Complexity Economics: A Different Framework for Economic Thought - W. Brian Arthur

Abstract
This paper provides a logical framework for complexity economics. Complexity economics builds from the proposition that the economy is not necessarily in equilibrium: economic agents (firms, consumers, investors) constantly change their actions and strategies in response to the outcome they mutually create. This further changes the outcome, which requires them to adjust afresh. Agents thus live in a world where their beliefs and strategies are constantly being “tested” for survival within an outcome or “ecology” these beliefs and strategies together create. Economics has largely avoided this nonequilibrium view in the past, but if we allow it, we see patterns or phenomena not visible to
equilibrium analysis. These emerge probabilistically, last for some time and dissipate, and they correspond to complex structures in other fields. We also see the economy not as something given and existing but forming from a constantly developing set of technological innovations, institutions, and arrangements that draw forth further innovations, institutions and arrangements.
Complexity economics sees the economy as in motion, perpetually “computing” itself—perpetually constructing itself anew. Where equilibrium economics emphasizes order, determinacy, deduction, and stasis, complexity economics emphasizes contingency, indeterminacy, sense-making, and openness to change. In this framework time, in the sense of real historical time, becomes important, and a solution is no longer necessarily a set of mathematical conditions but a pattern, a set
of emergent phenomena, a set of changes that may induce further changes, a set of existing entities creating novel entities. Equilibrium economics is a special case of nonequilibrium and hence complexity economics, therefore complexity economics is economics done in a more general way. It shows us an economy perpetually inventing itself, creating novel structures and possibilities for exploitation, and perpetually open to response.


Via Alessandro Cerboni
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Lorien Pratt's curator insight, December 14, 2013 8:40 PM

From the body of the paper:

Complexity economics is not a special case of neoclassical economics. On the contrary, equilibrium economics is a special case of nonequilibrium and hence complexity economics. Complexity economics, we can say, is economics done in a more general way. Equilibrium of course will remain a useful first-order approximation, useful for situations in economics that are well-defined, rationalizable, and reasonably static, but it can no longer claim to be the

center of economics.

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Scott Page on Leveraging Diversity


Via Viktor Markowski
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Viktor Markowski's curator insight, May 16, 2013 5:14 PM

One and a half hour of highly entertaining and high speed train thoughts on diversity and how to apply it.

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The scale of things

The scale of things | Non-Equilibrium Social Science | Scoop.it

Geoffrey West continually searches for underlying principles, the universal laws that explain why things tick. 

For many years, that meant working on the scale of tiny things—quarks and other subatomic particles. 

In the past 15-plus years, West has branched out. Still using a theoretical-physics-inspired approach, he and biology colleagues developed a quantitative, predictive framework to explain why scale-related relationships occur in biology, and he has extended it to cities, cancer and other subjects.

“I still very much consider myself a physicist because physics deals with fundamental questions at all scales, from the subatomic to the cosmos,” says West.

 

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Efficient discovery of overlapping communities in massive networks

Efficient discovery of overlapping communities in massive networks | Non-Equilibrium Social Science | Scoop.it

Detecting overlapping communities is essential to analyzing and exploring natural networks such as social networks, biological networks, and citation networks. However, most existing approaches do not scale to the size of networks that we regularly observe in the real world. In this paper, we develop a scalable approach to community detection that discovers overlapping communities in massive real-world networks. Our approach is based on a Bayesian model of networks that allows nodes to participate in multiple communities, and a corresponding algorithm that naturally interleaves subsampling from the network and updating an estimate of its communities. We demonstrate how we can discover the hidden community structure of several real-world networks, including 3.7 million US patents, 575,000 physics articles from the arXiv preprint server, and 875,000 connected Web pages from the Internet. Furthermore, we demonstrate on large simulated networks that our algorithm accurately discovers the true community structure. This paper opens the door to using sophisticated statistical models to analyze massive networks.


Via Claudia Mihai, Complexity Digest
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ComplexInsight's curator insight, December 31, 2013 4:02 AM

Network visualization tools like Gephi and analysis tools like SNAP are becoming essential components in understanding, mapping and comprehending inter-relating networks and network processes. This is a good paper that gives insight into appliying networking analysis tools to identify otherwise hidden community structures in apparhently disconnected or partially connected sets which will be hugely important in large scale network analysis.

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Spontaneous recovery in dynamical networks

Spontaneous recovery in dynamical networks | Non-Equilibrium Social Science | Scoop.it
Networks that fail can sometimes recover spontaneously[mdash]think of traffic jams suddenly easing or people waking from a coma.

Via Shaolin Tan, John Symons
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Exploring Humanity's Evolving 'Global Brain'

Exploring Humanity's Evolving 'Global Brain' | Non-Equilibrium Social Science | Scoop.it

What does collective intelligence mean? It’s important to realize that intelligence is not just something that happens inside individual brains. It also arises with groups of individuals. In fact, I’d define collective intelligence as groups of individuals acting collectively in ways that seem intelligent. By that definition, of course, collective intelligence has been around for a very long time. Families, companies, countries, and armies: those are all examples of groups of people working together in ways that at least sometimes seem intelligent.

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The Heart as a Complex Adaptive System

The Heart as a Complex Adaptive System | Non-Equilibrium Social Science | Scoop.it

There is mounting evidence that the heart is a system onto itself and that it is intimately intertwined with the nervous and endocrine system residing within its borders. The capacity of self-organized systems to adapt is embodied in the functional organization of the intrinsic control mechanisms. How these regulatory subsystems communicate and how uncoupling of the hierarchical organization results in loss of adaptive "fitness"remains a challenge in human biology. The principles by which "emergent properties" and functional order of a self-organizingsystem, such as the heart, achieve (homeo)dynamic stability provide a non-reductionist framework for understanding how biological system adapts to imposed internal and external stresses, e.g., ischemia, organ/tissue transplantation. In particular, the newly emergent dynamics of cardiac rhythm observed after the heart is transplanted may reflect a more stable,versatile and adaptive (as per "law of requisite variety") bipartite whole. The integrative action of the living organism can not be gotten from their concatenated fractions but is evolved "relationally", i.e., it emanates from emergent internal requirements of the constitutive parts.

J. Yasha Kresh, Igor Izrailtyan, Andrew S. Wechsler 
Depts. of Cardiothoracic Surgery and Medicine 
MCP-Hahnemann School of Medicine / Drexel University, Philadelphia, PA


Via Bernard Ryefield, John Symons
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John Symons's curator insight, December 19, 2013 12:23 PM

deeply interesting study of the dynamics of the heart.  

june holley's curator insight, January 7, 8:09 AM

The heart can help us understand self-organization.

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Digital global intelligence on the future of the world in the palm of your hand

Digital global intelligence on the future of the world in the palm of your hand | Non-Equilibrium Social Science | Scoop.it

The Millennium Project’s Global Futures Intelligence System is now available and accessible online, including auto-detected mobile phone data access.

“Overviews, situation charts, references, and latest relevant news on the most important challenges facing humanity are now all immediately available,” explains Jerome Glenn, CEO of The Millennium Project.

“The system presents distillations of the present situation, prospects, and strategies to address issues ranging from climate change to governance, science and technology, economics, ethics, education and other areas, with more than 10,000 pages of research, charts, and graphs available.”

“This is a fabulous tool to clarify the complexity of the world; you don’t have to go all over the Internet to understand something; this gets it all together,” said Philippe Destatte, Director of The Destree Institute (Namur, Wallonia) and a sponsor of the Brussels launch of the Global Futures Intelligence System held at Royal Academy of Belgium along with the Club of Rome European Union Chapter and Deloitte.


Via Spaceweaver
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mtmeme's curator insight, December 17, 2013 8:05 PM

Data must be free!

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Philosophy of Complex Systems (Book in PDF)


Via John Symons, António F Fonseca
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New book: "Hypernetworks in the Science of Complex Systems", by Jeffrey Johnson (World Scientific)

New book: "Hypernetworks in the Science of Complex Systems", by Jeffrey Johnson (World Scientific) | Non-Equilibrium Social Science | Scoop.it

The modern world is complex beyond human understanding and control. The science of complex systems aims to find new ways of thinking about the many interconnected networks of interaction that defy traditional approaches. Thus far, research into networks has largely been restricted to pairwise relationships represented by links between two nodes. This volume marks a major extension of networks to multidimensional hypernetworks for modeling multi-element relationships, such as companies making up the stock market, the neighborhoods forming a city, people making up committees, divisions making up companies, computers making up the internet, men and machines making up armies, or robots working as teams.

This volume makes an important contribution to the science of complex systems by: (i) extending network theory to include dynamic relationships between many elements; (ii) providing a mathematical theory able to integrate multilevel dynamics in a coherent way; (iii) providing a new methodological approach to analyze complex systems; and (iv) illustrating the theory with practical examples in the design, management and control of complex systems taken from many areas of application.


Via Jorge Louçã
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Hypernetwork Theory might become an essential component of the new Non-Equilibrium Social Systems Science

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What social networks know about you.

What social networks know about you. | Non-Equilibrium Social Science | Scoop.it

It’s hard to escape the sense that we provide social networks with too much information about ourselves. They know our names, our faces, our friends, our favorite music and movies, our employment history. Since they profit by using our online identities to sell targeted advertising, it’s only fair to ask how networks like Facebook, Twitter, and Instagram view us.


Via Artur Alves
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Artur Alves's curator insight, December 17, 2013 5:43 AM

This infographic shows how much of your information is stored, sorted and used by your social network services.

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Welcome to the new reputation economy

Welcome to the new reputation economy | Non-Equilibrium Social Science | Scoop.it
Your every online transaction requires you to establish your trustworthiness. That’s why your personal reputation dashboard will soon matter more than your credit record
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Complex Adaptive Systems clipboard magazine

Complex Adaptive Systems clipboard magazine | Non-Equilibrium Social Science | Scoop.it
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Rescooped by NESS from Complexity - Complex Systems Theory
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Simple mathematical law benchmarks human confrontations

Simple mathematical law benchmarks human confrontations | Non-Equilibrium Social Science | Scoop.it

Many high-profile societal problems involve an individual or group repeatedly attacking another - from child-parent disputes, sexual violence against women, civil unrest, violent conflicts and acts of terror, to current cyber-attacks on national infrastructure and ultrafast cyber-trades attacking stockholders. There is an urgent need to quantify the likely severity and timing of such future acts, shed light on likely perpetrators, and identify intervention strategies. Here we present a combined analysis of multiple datasets across all these domains which account for >100,000 events, and show that a simple mathematical law can benchmark them all. We derive this benchmark and interpret it, using a minimal mechanistic model grounded by state-of-the-art fieldwork. Our findings provide quantitative predictions concerning future attacks; a tool to help detect common perpetrators and abnormal behaviors; insight into the trajectory of a 'lone wolf'; identification of a critical threshold for spreading a message or idea among perpetrators; an intervention strategy to erode the most lethal clusters; and more broadly, a quantitative starting point for cross-disciplinary theorizing about human aggression at the individual and group level, in both real and online worlds.


Via Bernard Ryefield
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Communicating Social Simulation Models to Sceptical Minds

Communicating Social Simulation Models to Sceptical Minds | Non-Equilibrium Social Science | Scoop.it

Annie Waldherr and Nanda Wijermans (2013)

Journal of Artificial Societies and Social Simulation 16 (4) 13
http://jasss.soc.surrey.ac.uk/16/4/13.html

Published: 31-Oct-2013

 

When talking to fellow modellers about the feedback we get on our simulation models the conversation quickly shifts to anecdotes of rejective scepticism. Many of us experience that they get only few remarks, and especially only little helpful constructive feedback on their simulation models. In this forum paper, we give an overview and reflections on the most common criticisms experienced by ABM modellers. Our goal is to start a discussion on how to respond to criticism, and particularly rejective scepticism, in a way that makes it help to improve our models and consequently also increase acceptance and impact of our work. We proceed by identifying common criticism on agent-based modelling and social simulation methods and show where it shifts to rejection. In the second part, we reflect on the reasons for rejecting the agent-based approach, which we mainly locate in a lack of understanding on the one hand, and academic territorialism on the other hand. Finally, we also give our personal advice to socsim modellers of how to deal with both forms of rejective criticism.

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Lorien Pratt's curator insight, December 12, 2013 10:02 PM

What an interesting topic!  I agree wholeheartedly with the premise underlying this paper, which is that it's important to focus explicitly on the factors that lead to model acceptance and that overcome skepticism and rejection.

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Complexity map - Brian Castellani - Dec. 5 update

Complexity map - Brian Castellani - Dec. 5 update | Non-Equilibrium Social Science | Scoop.it

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