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Social Factors in Epidemiology

Despite the invention of control measures like vaccines, infectious diseases remain part of human existence. Ideas, sentiments, or information can also be contagious. Such social contagion is akin to biological contagion: Both spread through a replication process that is blind to the consequences for the individual or population, and if each person transmits to more than one person, the explosive power of exponential growth creates an epidemic. Social contagions may cause irrational “fever.” Isaac Newton, having lost £20,000 in the speculative South Sea Bubble, commented that he could “calculate the movement of the stars, but not the madness of men”. Systems in which both contagion types are coupled to one another—an infectious disease spreading by biological contagion and a social contagion concerning the disease—offer unique scientific challenges and are increasingly important for public health.

 

Social Factors in Epidemiology

Chris T. Bauch, Alison P. Galvani

Science 4 October 2013:
Vol. 342 no. 6154 pp. 47-49
http://dx.doi.org/10.1126/science.1244492


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Arjen ten Have's curator insight, October 8, 2013 3:04 PM

likely a better model of how ideas spread thru society than memes as genes

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Universal Power Law Governing Pedestrian Interactions

Universal Power Law Governing Pedestrian Interactions | Sistemas complejos | Scoop.it

Human crowds often bear a striking resemblance to interacting particle systems, and this has prompted many researchers to describe pedestrian dynamics in terms of interaction forces and potential energies. The correct quantitative form of this interaction, however, has remained an open question. Here, we introduce a novel statistical-mechanical approach to directly measure the interaction energy between pedestrians. This analysis, when applied to a large collection of human motion data, reveals a simple power law interaction that is based not on the physical separation between pedestrians but on their projected time to a potential future collision, and is therefore fundamentally anticipatory in nature. Remarkably, this simple law is able to describe human interactions across a wide variety of situations, speeds and densities. We further show, through simulations, that the interaction law we identify is sufficient to reproduce many known crowd phenomena.

 

 

Universal Power Law Governing Pedestrian Interactions
Phys. Rev. Lett. 113, 238701 – Published 2 December 2014
Ioannis Karamouzas, Brian Skinner, and Stephen J. Guy

http://dx.doi.org/10.1103/PhysRevLett.113.238701


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Liz Rykert's curator insight, December 13, 9:19 PM

Love this kind of research describing the actual patterns of interaction, in this case the space between pedestrians described as the time to potential collision!

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Percolation and cooperation with mobile agents: Geometric and strategy clusters

Percolation and cooperation with mobile agents: Geometric and strategy clusters | Sistemas complejos | Scoop.it
We study the conditions for persistent cooperation in an off-lattice model of mobile agents playing the Prisoner's Dilemma game with pure, unconditional strategies. Each agent has an exclusion radius ${r}_{P}$, which accounts for the population viscosity, and an interaction radius ${r}_{\mathrm{int}}$, which defines the instantaneous contact network for the game dynamics. We show that, differently from the ${r}_{P}=0$ case, the model with finite-sized agents presents a coexistence phase with both cooperators and defectors, besides the two absorbing phases, in which either cooperators or defectors dominate. We provide, in addition, a geometric interpretation of the transitions between phases. In analogy with lattice models, the geometric percolation of the contact network (i.e., irrespective of the strategy) enhances cooperation. More importantly, we show that the percolation of defectors is an essential condition for their survival. Differently from compact clusters of cooperators, isolated groups of defectors will eventually become extinct if not percolating, independently of their size.

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The Matthew effect in empirical data

The Matthew effect describes the phenomenon that in societies the rich tend to get richer and the potent even more powerful. It is closely related to the concept of preferential attachment in network science, where the more connected nodes are destined to acquire many more links in the future than the auxiliary nodes. Cumulative advantage and success-breads-success also both describe the fact that advantage tends to beget further advantage. The concept is behind the many power laws and scaling behaviour in empirical data, and it is at the heart of self-organization across social and natural sciences. Here we review the methodology for measuring preferential attachment in empirical data, as well as the observations of the Matthew effect in patterns of scientific collaboration, socio-technical and biological networks, the propagation of citations, the emergence of scientific progress and impact, career longevity, the evolution of common English words and phrases, as well as in education and brain development. We also discuss whether the Matthew effect is due to chance or optimisation, for example related to homophily in social systems or efficacy in technological systems, and we outline possible directions for future research.

 

The Matthew effect in empirical data
Matjaz Perc

http://arxiv.org/abs/1408.5124


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Sand Pile Model of the Mind Grows in Popularity

Sand Pile Model of the Mind Grows in Popularity | Sistemas complejos | Scoop.it
Support is growing for a decades-old physics idea suggesting that localized episodes of disordered brain activity help keep the overall system in healthy balance

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Self-organization in complex systems as decision making

The idea is advanced that self-organization in complex systems can be treated as decision making (as it is performed by humans) and, vice versa, decision making is nothing but a kind of self-organization in the decision maker nervous systems. A mathematical formulation is suggested based on the definition of probabilities of system states, whose particular cases characterize the probabilities of structures, patterns, scenarios, or prospects. In this general framework, it is shown that the mathematical structures of self-organization and of decision making are identical. This makes it clear how self-organization can be seen as an endogenous decision making process and, reciprocally, decision making occurs via an endogenous self-organization. The approach is illustrated by phase transitions in large statistical systems, crossovers in small statistical systems, evolutions and revolutions in social and biological systems, structural self-organization in dynamical systems, and by the probabilistic formulation of classical and behavioral decision theories. In all these cases, self-organization is described as the process of evaluating the probabilities of macroscopic states or prospects in the search for a state with the largest probability. The general way of deriving the probability measure for classical systems is the principle of minimal information, that is, the conditional entropy maximization under given constraints. Behavioral biases of decision makers can be characterized in the same way as analogous to quantum fluctuations in natural systems

 

Self-organization in complex systems as decision making
V.I. Yukalov, D. Sornette
arXiv:1408.1529, 2014
http://arxiv.org/abs/1408.1529


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Eli Levine's curator insight, August 16, 1:28 PM

Basically, the process of decision-making is apart of the system as a whole and not an externality. Where is the clear distinction between a user and the computer program that they choose to run? Can't it all be viewed as one thing? 

 

Amazing implications for governing and government relative to society. 

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One rule of life: Are we poised on the border of order?

WHEN physicists take an interest in the living world, some biologists fear the worst. After all, goes the bad joke, there's only so much you can gain by modelling a cow as a sphere. But one crucial idea from physics may hold valuable insights into complex biological behaviour in everything from birds to gene networks. There is increasing evidence that many systems we observe in living things are close to what's called a critical point – they sit on a knife-edge, precariously poised between order and disorder. Odd as it may sound, this strategy could confer a variety of benefits, in particular the flexibility to deal with a complex and unpredictable environment.

 

http://www.newscientist.com/article/mg22229660.700-one-rule-of-life-are-we-poised-on-the-border-of-order.html ;

 

Draft at http://philipball.blogspot.mx/2014/04/criticality-and-phase-transitions-in.html

 


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Eli Levine's curator insight, May 4, 12:14 AM

Indeed, what is biology but a manifestation of physical laws and matter?

 

Makes sense to me, very much like it makes sense to have physicists look at the principles underpinning societies, markets and organizations of people.

Think about it.

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Complexity Explorer -- Resources

The Resources section contains annotated links to a wide variety of web-based resources related to complex systems. These include journals, conferences, tutorials, software, videos, among other types of resources that will be useful for all levels of interest.


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Agent-based modeling and simulation of emergent behavior in air transportation

Agent-based modeling and simulation of emergent behavior in air transportation | Sistemas complejos | Scoop.it

Commercial aviation is feasible thanks to the complex socio-technical air transportation system, which involves interactions between human operators, technical systems, and procedures. In view of the expected growth in commercial aviation, significant changes in this socio-technical system are in development both in the USA and Europe. Such a complex socio-technical system may generate various types of emergent behavior, which may range from simple emergence, through weak emergence, up to strong emergence. The purpose of this paper is to demonstrate that agent-based modeling and simulation allows identifying changed and novel rare emergent behavior in this complex socio-technical system.


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Introduction to Complex Systems: Patterns in Nature

This video provides a basic introduction to the science of complex systems, focusing on patterns in nature. (For more information on agent-based modeling, vi...

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António F Fonseca's curator insight, February 1, 4:50 AM

Agent based modeling still is the best tool to understand complex systems when mathematical modeling gets very complicated.

Liz Rykert's curator insight, February 10, 7:25 PM

Always looking for good resources to introduce complexity science to others. This looks great. 

Ian Biggs, MAIPM, CPPE's curator insight, April 16, 8:08 PM

I recently conducted a series of workshops on the subject of 'Complex Project Management - Navigating through the unknown'. This clip provides a great introduction to complex systems and for those interested in Complexity Science, this clip is worth 7:52 of your time.

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éToile Platform

éToile Platform | Sistemas complejos | Scoop.it

The éToile Platform is an open, interactive, new way of sharing educational resources for Master and PhD levels in Complexity Sciences domains.

In different modules, students and researchers can:

check their knowledge using the étoile evaluation tests;interact with other people studying the same subjects;use the éToile facilities for studying and researching on the Internet;contribute for an ecology of pedagogical resources;certificated their mastery of a core curriculum in Complexity Sciences;interact with a worldwide community of students and scientific researchers within the CS-Digital Campus.


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António F Fonseca's curator insight, January 22, 4:47 AM

Portugal is on the first front in Complex Systems Studies.

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Complex systems: Ecology for bankers : Article : Nature

Complex systems: Ecology for bankers : Article : Nature | Sistemas complejos | Scoop.it

There is common ground in analysing financial systems and ecosystems, especially in the need to identify conditions that dispose a system to be knocked from seeming stability into another, less happy state.


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Chaos Forgets and Remembers: Measuring Information Creation, Destruction, and Storage

The hallmark of deterministic chaos is that it creates information—the rate being given by the Kolmogorov-Sinai metric entropy. Since its introduction half a century ago, the metric entropy has been used as a unitary quantity to measure a system’s intrinsic unpredictability. Here, we show that it naturally decomposes into two structurally meaningful components: A portion of the created information—the ephemeral information—is forgotten and a portion—the bound information—is remembered. The bound information is a new kind of intrinsic computation that differs fundamen- tally from information creation: it measures the rate of active information storage. We show that it can be directly and accurately calculated via symbolic dynamics, revealing a hitherto unknown richness in how dynamical systems compute.

 

Chaos Forgets and Remembers: Measuring Information Creation, Destruction, and Storage
Ryan G. James, Korana Burke, James P. Crutchfield

http://www.santafe.edu/research/working-papers/abstract/a0504be522643a0cc27e85bb3bf074e5/


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Nicholas Christakis: The #Sociological Science Behind Social #Networks and Social #Influence | #SNA

If You're So Free, Why Do You Follow Others? The Sociological Science Behind Social Networks and Social Influence. Nicholas Christakis, Professor of Medical ...


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luiy's curator insight, September 28, 7:44 PM

If you think you're in complete control of your destiny or even your own actions, you're wrong. Every choice you make, every behavior you exhibit, and even every desire you have finds its roots in the social universe. Nicholas Christakis explains why individual actions are inextricably linked to sociological pressures; whether you're absorbing altruism performed by someone you'll never meet or deciding to jump off the Golden Gate Bridge, collective phenomena affect every aspect of your life. By the end of the lecture Christakis has revealed a startling new way

Bill Aukett's curator insight, September 29, 8:34 PM

Human networks as complex systems?

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▶ Self-organizing Intelligent Network of UAVs - YouTube

This video explains our research on autonomous unmanned aerial vehicles (UAVs). The research team at the Alpen-Adria University and Lakeside Labs developing a multi-UAV system by four key components: - the multiple UAV platforms,

 

http://youtu.be/QX2UPkd6yIc


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The small-world effect is a modern phenomenon

The small-world effect is a modern phenomenon | Sistemas complejos | Scoop.it

The "small-world effect" is the observation that one can find a short chain of acquaintances, often of no more than a handful of individuals, connecting almost any two people on the planet. It is often expressed in the language of networks, where it is equivalent to the statement that most pairs of individuals are connected by a short path through the acquaintance network. Although the small-world effect is well-established empirically for contemporary social networks, we argue here that it is a relatively recent phenomenon, arising only in the last few hundred years: for most of mankind's tenure on Earth the social world was large, with most pairs of individuals connected by relatively long chains of acquaintances, if at all. Our conclusions are based on observations about the spread of diseases, which travel over contact networks between individuals and whose dynamics can give us clues to the structure of those networks even when direct network measurements are not available. As an example we consider the spread of the Black Death in 14th-century Europe, which is known to have traveled across the continent in well-defined waves of infection over the course of several years. Using established epidemiological models, we show that such wave-like behavior can occur only if contacts between individuals living far apart are exponentially rare. We further show that if long-distance contacts are exponentially rare, then the shortest chain of contacts between distant individuals is on average a long one. The observation of the wave-like spread of a disease like the Black Death thus implies a network without the small-world effect.


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A Brazilian Wunderkind Who Calms Chaos

A Brazilian Wunderkind Who Calms Chaos | Sistemas complejos | Scoop.it
Artur Avila’s solutions to ubiquitous problems in chaos theory have “changed the face of the field,” earning him Brazil’s first Fields Medal.

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The Fascinating World of Complex Systems

Part 1:             http://www.multimedia.ethz.ch/campus/zurichmeetsny/?doi=10.3930/ETHZ/AV-80b92958-97b0-4ad7-b07f-b15192931efc&autostart=false
 
Part 2:             http://www.multimedia.ethz.ch/campus/zurichmeetsny/?doi=10.3930/ETHZ/AV-1db36e67-b2d7-4229-8973-ef1bb54dde27&autostart=false
  
http://www.complexsys.org/publicprograms.html


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june holley's curator insight, July 9, 8:40 AM

Videos on complex systems.

Tom Cockburn's curator insight, July 17, 4:07 AM

Interesting

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Ancient food webs developed modern structure soon after mass extinction

Ancient food webs developed modern structure soon after mass extinction | Sistemas complejos | Scoop.it
Researchers from the Santa Fe Institute and the Smithsonian Institution have pieced together a highly detailed picture of feeding relationships among 700 mammal, bird, reptile, fish, insect, and plant species from a 48 million year old lake and forest ecosystem.

Their analysis of fossilized remains from the Messel deposit near Frankfurt, Germany, provides the most compelling evidence to date that ancient food webs were organized much like modern food webs. Their paper describing the research appears online and open access this week in Proceedings of the Royal Society B: Biological Sciences.


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Eli Levine's curator insight, March 20, 6:37 PM

There is, indeed, not much that is new in this world.

 

One would think that humans would learn to live in relative harmony with nature.


However, I do not think that the brain types of those with real political power (everyone from public to private elites), as well as the brain types of the people in the general pool of society are capable of doing this at this time.

 

Therefore, we are going to kill ourselves off in mass droves.

 

And we probably won't learn our lessons, in spite of the damage that we're going to inflict on ourselves.

 

Think about it.

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▶ Chaos, Complexity, and Public Policy

Irene Sanders Executive Director and Founder of the Washington Center for Complexity and Public Policy and author of "Strategic Thinking and the New Science: Planning in the Midst of Chaos, Complexity, and Change."

 

http://www.youtube.com/watch?v=KXxs-JtvkkQ


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Eli Levine's curator insight, February 11, 2:09 PM

A way cool panel discussion.  I wish I could be a full practitioner of this new, empirically based governing and political strategic thinking.

Liz Rykert's curator insight, February 12, 10:34 AM

Loving these new video resources for understanding complexity and it applications.

Luciano Lampi's curator insight, March 23, 9:16 PM

are our politicians aware of these concepts?

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Murray Gell-Mann: The Simple and the Complex

http://www.thinkingallowed.com/2mgellmann.html Nobel laureate Gell-Mann addresses the relationship...


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How Can the Study of Complexity Transform Our Understanding of the World?

How Can the Study of Complexity Transform Our Understanding of the World? | Sistemas complejos | Scoop.it

The “study of complexity” refers to the attempt to find common principles underlying the behavior of complex systems—systems in which large collections of components interact in nonlinear ways. Here, the term nonlinear implies that the system can’t be understood simply by understanding its individual components; nonlinear interactions cause the whole to be “more than the sum of its parts.”

 

How Can the Study of Complexity Transform Our Understanding of the World?

Melanie Mitchell

https://www.bigquestionsonline.com/content/how-can-study-complexity-transform-our-understanding-world


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António F Fonseca's curator insight, January 22, 4:45 AM

Wonderful and clarifying text.

Lorien Pratt's curator insight, January 22, 11:20 PM

One of my favorite complexity authors.  An excerpt: "In the past it was widely assumed that such phenomena are hard to predict because the underlying processes are highly complex, and that random factors must play a key role.  However, Complex Systems science—especially the study of dynamics and chaos—have shown that complex behavior and unpredictability can arise in a system even if the underlying rules are extremely simple and completely deterministic.  Often, the key to complexity is the iteration over time of simple, though nonlinear, interaction rules among the system’s components."


This insight is at the core of Decision Intelligence, which adds an understanding of these emergent behaviors to the usual big data/predictive analytics/optimization stack.

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Complexity map - Brian Castellani - Dec. 5 update

Complexity map - Brian Castellani - Dec. 5 update | Sistemas complejos | Scoop.it

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Barabási : The Hidden #Pattern Behind Everything We Do I #datascience #SNA


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ukituki's curator insight, November 24, 2013 8:35 AM

Barabasi argues that, rather than being random,
humans actually act in predictable patterns. We go along for long
periods of quiet routine followed suddenly by loud bursts of activity.
Barabasi demonstrates that these breaks in routine, or "bursts," are
present in all aspects of our existence— in the way we write emails,
spend our money, manage our health, form ideas. Barabasi has even
found "burstiness" in our webpage clicking activity and the online
news cycle."