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From Schelling to Schools

We address theoretically whether and under what conditions Schelling's celebrated result of 'self-organized' unintended residential segregation may also apply to school segregation. We propose here a computational model of school segregation that is aligned with a corresponding Schelling-type model of residential segregation. To adapt the model for application to school segregation, we move beyond previous work by combining two preference arguments in modeling parents' school choice, preferences for the ethnic composition of a school and preferences for minimizing the travelling distance to the school. In a set of computational experiments we assessed the effects of population composition and distance preferences in the school model. We found that a preference for nearby schools can suppress the trend towards self-organized segregation obtained in a baseline condition where parents were indifferent towards distance. We then investigated the joint effects of the variation of agents' 'tolerance' for out-group members and distance preference. We found that integrated distributions were preserved under a much broader range of conditions than in the absence of a preference for nearby schools. We conclude that parents' preferences for nearby schools may be an important factor in tempering for school choice the segregation dynamics known from models of residential segregation.

 

From Schelling to Schools: A Comparison of a Model of Residential Segregation with a Model of School Segregation

Victor Ionut Stoica and Andreas Flache

Journal of Artificial Societies and Social Simulation 17 (1) 5

http://jasss.soc.surrey.ac.uk/17/1/5.html ;


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Eli Levine's curator insight, February 11, 10:37 AM

It appears as if racial segregation begins with where you live and are able to live.  This then helps to perpetuate misunderstandings, bigotry and biases against people from other racial, ethnic and social backgrounds than yourself in many individual cases across the human spectrum.

 

It's a shame that, even now, we're still so tribal, just like our chimp ancestors.

 

Think about it.

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Information: A Personal Synthesis

This article is an attempt to capture, in a reasonable space, some of the major developments and currents of thought in information theory and the relations between them. I have particularly tried to include changes in the views of key authors in the field. The domains addressed range from mathematical-categorial, philosophical and computational approaches to systems, causal-compositional, biological and religious approaches and messaging theory. I have related key concepts in each domain to my non-standard extension of logic to real processes that I call Logic in Reality (LIR). The result is not another attempt at a General Theory of Information such as that of Burgin, or a Unified Theory of Information like that of Hofkirchner. It is not a compendium of papers presented at a conference, more or less unified around a particular theme. It is rather a highly personal, limited synthesis which nonetheless may facilitate comparison of insights, including contradictory ones, from different lines of inquiry. As such, it may be an example of the concept proposed by Marijuan, still little developed, of the recombination of knowledge. Like the best of the work to which it refers, the finality of this synthesis is the possible contribution that an improved understanding of the nature and dynamics of information may make to the ethical development of the information society.

 

Information: A Personal Synthesis
by Joseph Brenner
Information 2014, 5(1), 134-170; doi:10.3390/info5010134
http://www.mdpi.com/2078-2489/5/1/134/ ;


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Eli Levine's curator insight, April 11, 10:57 AM

All information that we receive from the universe that is around us is second hand.  It is possible to alter and shift them out of our own volition or of the volition of someone else, provided that we're either caught unawares or allowing it to happen just as it is theoretically possible to shift the universe around us, so that we experience something different than what would ordinarily happen (again, only theoretically, not necessarily in actuality).  The universe is out there, I think, just as we're most certainly apart of it.  There are laws to this place as well which influence and effect our abilities to act, our perception of the choices that we have and the choices that we actually are left with at the end of the day, when all's said and told.  We are just receptors, analyzers and synthesizers of information with our biological bodies.  We are all slaves, ultimately, to our biology, our circumstances and the consequences of our actions.

 

Just my two cents on information.

 

Think about it.

António F Fonseca's curator insight, April 12, 2:46 AM

Brenner and Daniel Cohnitz have a very good book about the subject "Information and Information Flow" that covers almost all aspects of Information Theory. Unfortunatelly the 'Matecmatical Information Theory' of Jan Kahre didn't have yet the same attention.

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The Future of Money Infographic | Visual.ly

The Future of Money Infographic | Visual.ly | Non-Equilibrium Social Science | Scoop.it
How social and mobile technologies are changing the way people earn,
manage and spend money.

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Ferananda's curator insight, April 14, 6:58 PM

Nice #infographic about #futureofmoney you can get a glance of how much is happening in the field.  Still money and #cashless means just that -no cash- yet...its movement towards changing rules. 

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ECCS'14 - submissions for contributed talks/posters

ECCS'14 - submissions for contributed talks/posters | Non-Equilibrium Social Science | Scoop.it

Submissions for contributed talks/posters will be open until April 15 2014. Acceptance will be communicated on April 30 2014 at the latest. Contributions must be submitted through EasyChair.org at the page https://www.easychair.org/conferences/?conf=eccs14

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Predicting Successful Memes using Network and Community Structure

Predicting Successful Memes using Network and Community Structure | Non-Equilibrium Social Science | Scoop.it

Via luiy, Shaolin Tan, António F Fonseca
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luiy's curator insight, March 27, 10:44 AM

We investigate the predictability of successful memes using their early spreading patterns in the underlying social networks. We propose and analyze a comprehensive set of features and develop an accurate model to predict future popularity of a meme given its early spreading patterns. Our paper provides the first comprehensive comparison of existing predictive frameworks. We categorize our features into three groups: influence of early adopters, community concentration, and characteristics of adoption time series. We find that features based on community structure are the most powerful predictors of future success. We also find that early popularity of a meme is not a good predictor of its future popularity, contrary to common belief. Our methods outperform other approaches, particularly in the task of detecting very popular or unpopular memes.

António F Fonseca's curator insight, April 2, 3:01 AM

Another paper about popularity prediction.

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Revealing the Hidden Language of Complex Networks

Revealing the Hidden Language of Complex Networks | Non-Equilibrium Social Science | Scoop.it
Sophisticated methods for analysing complex networks promise to be of great benefit to almost all scientific disciplines, yet they elude us. In this work, we make fundamental methodological advances to rectify this. We discover that the interaction between a small number of roles, played by nodes in a network, can characterize a network's structure and also provide a clear real-world interpretation. Given this insight, we develop a framework for analysing and comparing networks, which outperforms all existing ones. We demonstrate its strength by uncovering novel relationships between seemingly unrelated networks, such as Facebook, metabolic, and protein structure networks. We also use it to track the dynamics of the world trade network, showing that a country's role of a broker between non-trading countries indicates economic prosperity, whereas peripheral roles are associated with poverty. This result, though intuitive, has escaped all existing frameworks. Finally, our approach translates network topology into everyday language, bringing network analysis closer to domain scientists.
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Big data: are we making a big mistake?

Big data: are we making a big mistake? | Non-Equilibrium Social Science | Scoop.it

by Tim Harford

Five years ago, a team of researchers from Google announced a remarkable achievement in one of the world’s top scientific journals, Nature. Without needing the results of a single medical check-up, they were nevertheless able to track the spread of influenza across the US. What’s more, they could do it more quickly than the Centers for Disease Control and Prevention (CDC). Google’s tracking had only a day’s delay, compared with the week or more it took for the CDC to assemble a picture based on reports from doctors’ surgeries. Google was faster because it was tracking the outbreak by finding a correlation between what people searched for online and whether they had flu symptoms.

 

Not only was “Google Flu Trends” quick, accurate and cheap, it was theory-free. Google’s engineers didn’t bother to develop a hypothesis about what search terms – “flu symptoms” or “pharmacies near me” – might be correlated with the spread of the disease itself. The Google team just took their top 50 million search terms and let the algorithms do the work.

 

The success of Google Flu Trends became emblematic of the hot new trend in business, technology and science: “Big Data”. What, excited journalists asked, can science learn from Google?

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Using Complex Networks to Characterize International Business Cycles

Using Complex Networks to Characterize International Business Cycles | Non-Equilibrium Social Science | Scoop.it

Background

 

There is a rapidly expanding literature on the application of complex networks in economics that focused mostly on stock markets. In this paper, we discuss an application of complex networks to study international business cycles.

Methodology/Principal Findings

 

We construct complex networks based on GDP data from two data sets on G7 and OECD economies. Besides the well-known correlation-based networks, we also use a specific tool for presenting causality in economics, the Granger causality. We consider different filtering methods to derive the stationary component of the GDP series for each of the countries in the samples. The networks were found to be sensitive to the detrending method. While the correlation networks provide information on comovement between the national economies, the Granger causality networks can better predict fluctuations in countries’ GDP. By using them, we can obtain directed networks allows us to determine the relative influence of different countries on the global economy network. The US appears as the key player for both the G7 and OECD samples.


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Eli Levine's curator insight, March 29, 12:13 PM

These are the natural laws and connections which exist amongst various economies and within each economy.  This shows the interconnectedness of the whole planet's economy and can give predictions as to what could happen if one particular economy were to crash and fall into valuelessness for humanity.

 

It's interesting that this research comes at a time in our history when the natural laws of social interactions are being violated by governments and elite groups everywhere.  What will happen if discontent turns into unrest and rebellions in the United States?  What happens if the authority of governments ceases to be legitimate, to the point where violence and anarchy take their place.  What will happen to the economy if the rule of law is no longer abided, and the mob takes over to deal with the perceived injustices that the elite groups have committed against the general public?

 

What happens when the environment gives way and our societies are no longer able to support the populations that are present?  What happens when people are forced to either starve or fight?

 

That's the direction that we're headed towards, I'm afraid. 

Funny how it is that the conservatives from all parties who enacted these policies, are leading to the very destruction of society that they're so afraid of.  Funny how it is that things get more delicate and likely to change significantly as they cling to their image of how the past was (and it is just an image of the past, not the real world as it was, is or will be).

 

Silly brains.

 

Think about it.

António F Fonseca's curator insight, March 31, 3:34 AM

Crisis transmission, lookout for USA, Ireland and Spain!

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Complex networks analysis in socioeconomic models

This chapter aims at reviewing complex networks models and methods that were either developed for or applied to socioeconomic issues, and pertinent to the theme of New Economic Geography. After an introduction to the foundations of the field of complex networks, the present summary adds insights on the statistical mechanical approach, and on the most relevant computational aspects for the treatment of these systems. As the most frequently used model for interacting agent-based systems, a brief description of the statistical mechanics of the classical Ising model on regular lattices, together with recent extensions of the same model on small-world Watts-Strogatz and scale-free Albert-Barabasi complex networks is included. Other sections of the chapter are devoted to applications of complex networks to economics, finance, spreading of innovations, and regional trade and developments. The chapter also reviews results involving applications of complex networks to other relevant socioeconomic issues, including results for opinion and citation networks. Finally, some avenues for future research are introduced before summarizing the main conclusions of the chapter.


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Arrogant physicists — do they think economics is easy?

Arrogant physicists — do they think economics is easy? | Non-Equilibrium Social Science | Scoop.it

by Mark Buchanan in The Physics of Finance


Economist Chris House wonders why so many physicists are drawn to economics. It's a fair question, and it must seem strange -- perhaps irritating -- to see people from a foreign field intruding into your territory, fully convinced that they'll be able to help out even without formal economics training. They haven’t learned what you’ve worked hard to learn, and yet they still have such annoying confidence. The explanation, Chris suggests, is that physicists often believe they're mathematically superior to economists, and so might be able to sort out some big problems quite easily.

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The story of the Gömböc

The story of the Gömböc | Non-Equilibrium Social Science | Scoop.it

The defining feature of a Gömböc is the fact that it's got just two points of equilibrium: one is stable and the other is unstable. If you put a Gömböc down on a flat surface, resting on its stable equilibrium point, it will stay as it is. "Even if you kick it a little, it will come back to its resting position at the stable equilibrium point," says Domokos, a mathematician at Budapest University of Technology and Economics. "The other equilibrium point is unstable. You can balance the Gömböc at this point a bit like you can balance a pencil on its tip: the slightest push will make it fall over." It's impossible to balance a Gömböc on any other point: if you try, it will move off in a specific direction. That's why the Gömböc seems to have a life on its own: put it down at a non-equilibrium point, and it will start rolling around in a systematic way until it has reached the stable equilibrium position. In other words, the Gömböc is self-righting.

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Swarming in Biological and Related Systems

Swarming in Biological and Related Systems | Non-Equilibrium Social Science | Scoop.it

In the last 15 years, the collective motion of large numbers of self-propelled objects has become an increasingly active area of research. The examples of such collective motion abound: flocks of birds, schools of fish, swarms of insects, herds of animals etc. Swarming of living creatures is believed to be critical for the population survival under harsh conditions. The ability of motile microorganisms to communicate and coordinate their motion leads to the remarkably complex self-organized structures found in bacterial biofilms. Active intracellular transport of biological molecules within the cytoskeleton has a profound effect on the cell cycle, signaling and motility. In recent years, significant progress has also been achieved in the design of synthetic self-propelled particles. Their collective motion has many advantages for performing specific robotic tasks, such as collective cargo delivery or harvesting the mechanical energy of chaotic motion.

(...)

In this focus issue we have tried to assemble papers from leading experts which we hope will provide a current snapshot of this young and rapidly expanding field of research. They cover both theoretical and experimental investigations of the dynamics of active matter on different spatial and temporal scales.

 

Focus on Swarming in Biological and Related Systems
Lev Tsimring, Hugues Chate, Igor Aronson

2014 New J. Phys. 16

http://iopscience.iop.org/1367-2630/focus/Focus%20on%20Swarming%20in%20Biological%20and%20Related%20Systems


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Why Model? Joshua M. Epstein

Why Model? Joshua M. Epstein | Non-Equilibrium Social Science | Scoop.it

This lecture treats some enduring misconceptions about modeling. One of these is that the goal is always prediction. The lecture distinguishes between explanation and prediction as modeling goals, and offers sixteen reasons other than prediction to build a model. It also challenges the common assumption that scientific theories arise from and 'summarize' data, when often, theories precede and guide data collection; without theory, in other words, it is not clear what data to collect. Among other things, it also argues that the modeling enterprise enforces habits of mind essential to freedom. It is based on the author's 2008 Bastille Day keynote address to the Second World Congress on Social Simulation, George Mason University, and earlier addresses at the Institute of Medicine, the University of Michigan, and the Santa Fe Institute.


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António F Fonseca's curator insight, March 23, 2:20 AM

The classical paper about modelling and simulation. Very clear.

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ECCS’14 European Conference on Complex Systems

ECCS’14 European Conference on Complex Systems | Non-Equilibrium Social Science | Scoop.it

ECCS’14 will be a major international conference and event in the area of complex systems and interdisciplinary science in general. It will offer unique opportunities to study novel scientific approaches in a multitude of application areas. Two days of the conference, 24 and 25 of September, are reserved for satellite meetings, which will cover a broad range of subjects on all aspects of Complex Systems, as reflected by the conference tracks.

 

ECCS’14 European Conference on Complex Systems

Lucca, Italy

2014-09-22:26

http://www.eccs14.eu

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Massive Data Flow: Understanding the Complex Dynamics of the Web

The Web is perhaps the most complex system that we know. Its massive scale, complex dynamism, open richness, and social character mean that it may be more profitable to study it using tools and concepts appropriate for understanding nervous systems, organisms, ecosystems and society, rather than approaches more traditionally employed to engineer technology. Simultaneously, the scientists trying to understand this wide array of complex natural systems may have much to gain by considering the emergingstudy of the Web.

 

Massive Data Flow: Understanding the Complex Dynamics of the Web
Workshop at the ACM Web Science Conference 2014 (http://www.websci14.org )
10:00 - 18:00, June 23rd, 2014
Indiana University, Bloomington

http://sacral.c.u-tokyo.ac.jp/event/MDF_WebSci/ ;


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Joseph E. Stiglitz asks what role government should play as economic restructuring proceeds

Joseph E. Stiglitz asks what role government should play as economic restructuring proceeds | Non-Equilibrium Social Science | Scoop.it
Many of China’s problems today stem from too much market and too little government. Or, to put it another way, while the government is clearly doing some things that it should not, it is also not doing some things that it should.
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Eli Levine's curator insight, April 2, 2:03 PM

Unfortunately, the CCP quashed the Populists under Bo Xilai and put into power a conservative who only seems concerned with tightening things under him while neglecting to effectively tend to the problems within his society and geographical territory.  Lots of sword rattling against Japan, the Philippines, and Vietnam; lots of putting down dissidents and Tibetan/Uigher nationalists.  There are some high profile corruption cases being put out.  However, nothing systemic or far reaching or sustainable seems to be being done for the sake of the people of China.  One would wonder what would indeed happen to the reigns of the CCP if they let market liberalization allocate resources out of the hands of the CCP members, such that new factions take ownership.  China is not a country that has historically done well when a multitude of factions are competing for the centralized control of the government.  One can only shudder at the implications for the rest of the world's economy and geo-political/social-political orders as a result of that kind of collapse.

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Topics in social network analysis and network science

This chapter introduces statistical methods used in the analysis of social networks and in the rapidly evolving parallel-field of network science. Although several instances of social network analysis in health services research have appeared recently, the majority involve only the most basic methods and thus scratch the surface of what might be accomplished. Cutting-edge methods using relevant examples and illustrations in health services research are provided.

by A. James O'Malley, Jukka-Pekka Onnela

arXiv:1404.0067 [physics.soc-ph]

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Eli Levine's curator insight, April 16, 3:08 PM

A very cool and comprehensive look at how networks can be analyzed, studied and examined.

 

Way cool science!

 

Think about it.

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Network communities within and across borders

Network communities within and across borders | Non-Equilibrium Social Science | Scoop.it
We investigate the impact of borders on the topology of spatially embedded networks. Indeed territorial subdivisions and geographical borders significantly hamper the geographical span of networks thus playing a key role in the formation of network communities. This is especially important in scientific and technological policy-making, highlighting the interplay between pressure for the internationalization to lead towards a global innovation system and the administrative borders imposed by the national and regional institutions. In this study we introduce an outreach index to quantify the impact of borders on the community structure and apply it to the case of the European and US patent co-inventors networks. We find that (a) the US connectivity decays as a power of distance, whereas we observe a faster exponential decay for Europe; (b) European network communities essentially correspond to nations and contiguous regions while US communities span multiple states across the whole country without any characteristic geographic scale. We confirm our findings by means of a set of simulations aimed at exploring the relationship between different patterns of cross-border community structures and the outreach index.
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Dynamical Systems on Networks: A Tutorial

We give a tutorial for the study of dynamical systems on networks, and we focus in particular on ``simple" situations that are tractable analytically. We briefly motivate why examining dynamical systems on networks is interesting and important. We then give several fascinating examples and discuss some theoretical results. We also discuss dynamical systems on dynamical (i.e., time-dependent) networks, overview software implementations, and give our outlook on the field.


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A map of the limits of statistics

A map of the limits of statistics | Non-Equilibrium Social Science | Scoop.it

by By Nassim Nicholas Taleb

Statistical and applied probabilistic knowledge is the core of knowledge; statistics is what tells you if something is true, false, or merely anecdotal; it is the "logic of science"; it is the instrument of risk-taking; it is the applied tools of epistemology; you can't be a modern intellectual and not think probabilistically—but... let's not be suckers. The problem is much more complicated than it seems to the casual, mechanistic user who picked it up in graduate school. Statistics can fool you. In fact it is fooling your government right now. It can even bankrupt the system (let's face it: use of probabilistic methods for the estimation of risks did just blow up the banking system).

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“It’s not the economy, stupid, it’s the narrative!” | Paul Ormerod

“It’s not the economy, stupid, it’s the narrative!” | Paul Ormerod | Non-Equilibrium Social Science | Scoop.it

(...) A narrative in which people believe is the key to electoral success, much more so than the objective economic facts. During the long period of Conservative rule from 1951-64, for example, people genuinely ‘never had it so good’, in Harold Macmillan’s famous phrase. But the Labour leader, Harold Wilson, was able to convince the nation that the Tories were decrepit, and what Britain needed was the ‘white heat of the technological revolution’.

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Eli Levine's curator insight, March 27, 1:48 PM

The funny part about this, is that the Democrats have the technical "right" ideas about how the government can positively effect the economy, even if they don't have a lot of the specifics down yet, and are too busy lounging in the malevolent embrace of the rich and the well to do.

 

Laissez-faire only creates conditions where wealth gets sucked into the maw of the already wealthy.  This inhibits growth, well being and people's abilities to pursue happiness.  It enables the disintegration of the social fabric and the environment that we all depend on for our well being and our survival.  This is what happened in the 1920's, the 1880's, and now in the 1980's through the 2010's.  The Gilded Age leads primarily an era of its own destruction.  You'd think people would learn.

 

But they don't.

 

Think about it.

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Team examines city life on the urban continuum

Over the past few centuries, human societies have changed dramatically. We travel, make things, treat illnesses and communicate in ways our ancestors could have never imagined.

All this has led some to conclude that human societies are fundamentally different today than they were in the past, but I’m not so sure. Some research I’ve been doing lately suggests just the opposite: Our technologies might have changed in amazing ways, but our societies still follow some of the same basic rules that shaped ancient civilizations.

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Eli Levine's curator insight, March 24, 7:04 PM

"History doesn't repeat itself, but it does rhyme." -Mark Twain

 

It's all organic to us, as a species.  It makes sense that it gets replicated across time and space, culture and nation.

 

This is indeed a more mathematical universe than we could ever have expected.

 

Let's hope that we're able to use this knowledge and technology and put it to good use, before the psychopaths of our current elite and the idiot cattle of our masses destroy our world through their actions and lack of action.

 

Think about it.

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Hypernetworks in the Science of Complex Systems (by Jeffrey Johnson)

Hypernetworks in the Science of Complex Systems (Series on Complexity Science)

~ Jeffrey Johnson (author) More about this product
List Price: $128.00
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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.


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june holley's curator insight, March 24, 5:36 AM

A little pricey but breakthrough stuff here...

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Four steps to fixing inequality

Four steps to fixing inequality | Non-Equilibrium Social Science | Scoop.it

By most measures, and in many countries, income inequality has been increasing for a generation. Some people don’t care, so here’s another way to look at the problem: over the past 20 years, the pre-tax incomes of the poorest 99 per cent in the US grew by just 6.6 per cent after adjusting for inflation. That is a pathetic one-third of 1 per cent per year. Those who aren’t worried about increasing inequality should still be concerned at such widespread stagnation of living standards.

So what is the solution? Here is a modest proposal to fix inequality in four easy steps.

 
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The Ecology of Collective Behavior

Similar patterns of interaction, such as network motifs and feedback loops, are used in many natural collective processes, probably because they have evolved independently under similar pressures. Here I consider how three environmental constraints may shape the evolution of collective behavior: the patchiness of resources, the operating costs of maintaining the interaction network that produces collective behavior, and the threat of rupture of the network. The ants are a large and successful taxon that have evolved in very diverse environments. Examples from ants provide a starting point for examining more generally the fit between the particular pattern of interaction that regulates activity, and the environment in which it functions.

 

Gordon DM (2014) The Ecology of Collective Behavior. PLoS Biol 12(3): e1001805. http://dx.doi.org/10.1371/journal.pbio.1001805

 


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Behavioural economics and public policy

Behavioural economics and public policy | Non-Equilibrium Social Science | Scoop.it
The past decade has been a triumph for behavioural economics, the fashionable cross-breed of psychology and economics. First there was the award in 2002 of the Nobel Memorial Prize in economics to a psychologist, Daniel Kahneman – the man who did as
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