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Structure and Dynamics of Information Pathways in Online Media

Diffusion of information, spread of rumors and infectious diseases are all instances of stochastic processes that occur over the edges of an underlying network. Many times networks over which contagions spread are unobserved, and such networks are often dynamic and change over time. In this paper, we investigate the problem of inferring dynamic networks based on information diffusion data. We assume there is an unobserved dynamic network that changes over time, while we observe the results of a dynamic process spreading over the edges of the network. The task then is to infer the edges and the dynamics of the underlying network.


We develop an on-line algorithm that relies on stochastic convex optimization to efficiently solve the dynamic network inference problem. We apply our algorithm to information diffusion among 3.3 million mainstream media and blog sites and experiment with more than 179 million different pieces of information spreading over the network in a one year period. We study the evolution of information pathways in the online media space and find interesting insights. Information pathways for general recurrent topics are more stable across time than for on-going news events. Clusters of news media sites and blogs often emerge and vanish in matter of days for on-going news events. Major social movements and events involving civil population, such as the Libyan's civil war or Syria's uprise, lead to an increased amount of information pathways among blogs as well as in the overall increase in the network centrality of blogs and social media sites.


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Stigmergy

Stigmergy | Information, Complexity, Computation | Scoop.it
This article is part of a series: ‘Governance and other systems of mass collaboration’. Stigmergy is a mechanism of indirect coordination between agents or actions. The principle is tha...
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Nature, nurture and liberal values

Nature, nurture and liberal values | Information, Complexity, Computation | Scoop.it

Human beings are diverse and live in diverse ways. Should we accept that we are diverse by nature, having followed separate evolutionary paths? Or should we suppose that we share our biological inheritance, but develop differently according to environment and culture? Over recent years scientific research has reshaped this familiar “nature-nurture” debate, which remains central to our understanding of human nature and morality.

 

For much of the 20th century social scientists held that human life is a single biological phenomenon, which flows through the channels made by culture, so as to acquire separate and often mutually inaccessible forms. Each society passes on the culture that defines it, much as it passes on its language. And the most important aspects of culture—religion, rites of passage and law—both unify the people who adhere to them and divide those people from everyone else. Such was implied by what John Tooby and Leda Cosmides called the “standard social science model,” made fundamental to anthropology by Franz Boas and to sociology by Émile Durkheim.

 

More recently evolutionary psychologists have begun to question that approach. Although you can explain the culture of a tribe as an inherited possession, they suggested, this does not explain how culture came to be in the first place. What is it that endows culture with its stability and function? In response to that question the opinion began to grow that culture does not provide the ultimate explanation of any significant human trait, not even the trait of cultural diversity. It is not simply that there are extraordinary constants among cultures: gender roles, incest taboos, festivals, warfare, religious beliefs, moral scruples, aesthetic interests. Culture is also a part of human nature: it is our way of being. We do not live in herds or packs; our hierarchies are not based merely on strength or sexual dominance. We relate to one another through language, morality and law; we sing, dance and worship together, and spend as much time in festivals and storytelling as in seeking our food. Our hierarchies involve offices, responsibilities, gift-giving and ceremonial recognition. Our meals are shared, and food for us is not merely nourishment but an occasion for hospitality, affection and dressing up. All these things are comprehended in the idea of culture—and culture, so understood, is observed in all and only human communities. Why is this?


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Were Weirdo Ediacarans Really Lichens, Fungi, and Slime Molds?

Were Weirdo Ediacarans Really Lichens, Fungi, and Slime Molds? | Information, Complexity, Computation | Scoop.it

Does these look like lichens to you? According to Gregory Retallack, they should.

 

Yesterday, Nature published an article by Retallack that makes a radical claim: the Ediacaran Biota (635-542 mya) of bizarre creatures that preceded the Cambrian Explosion were not pneumatic semi-mobile marine animals, but instead sessile land-dwelling lichens and protists living high and very much dry on land.

 

For those of us raised on pictures and dioramas of puffy Ediacaran animals ensconced happily on the seafloor, this is a bit of a shocker. Although scientists in the past have suggested that they *might* be giant marine protists, Retallack seems to be alone in carrying the lichen torch.

 

His analysis of the rock surrounding the fossils suggests to him the soil of dry land, and his analysis of cross sections of these fossils to him suggests lichen rootlets and biological soil crusts. Lichens today are symbiotic associations of fungi and algae.

 

You’ve probably seen a few in your time plastered to rocks, tombstones, or tree bark. Biological soil crusts are loose associations of cyanobacteria, algae, fungi, lichens, mosses familiar to those of us who live in the west*. They may represent some sort of proto-lichens or lichen incubators.


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Biological Computation - Microsoft Research

Biological Computation - Microsoft Research | Information, Complexity, Computation | Scoop.it
Application and development of computational methods and tools for modeling and analyzing complex biological systems.
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I think there will be many problems to solve here.

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ScienceDirect.com - Animal Behaviour - Individual memory and the emergence of cooperation

ScienceDirect.com - Animal Behaviour - Individual memory and the emergence of cooperation | Information, Complexity, Computation | Scoop.it
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Is Science Mostly Driven by Ideas or by Tools?

We are standing now as we stood in the 1950s, between a Kuhnian dream of sudden illumination and a Galisonian reality of laborious exploring. On one side are string theory and speculations about multiverses; on the other are all-sky surveys and observations of real black holes. The balance today is more even than it was in the 1950s. String theory is a far more promising venture than Einstein's unified field theory. Kuhn and Galison are running neck and neck in the race for glory. We are lucky to live in a time when both are going strong.

Is Science Mostly Driven by Ideas or by Tools?
Freeman J. Dyson
Science 14 December 2012:
Vol. 338 no. 6113 pp. 1426-1427
http://dx.doi.org/10.1126/science.1232773
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A portrait of Earth’s dirty atmosphere | ExtremeTech

A portrait of Earth’s dirty atmosphere | ExtremeTech | Information, Complexity, Computation | Scoop.it
Here's a mind-blowing view of the Earth that you've probably never seen -- or even thought of -- before. Dubbed
Eugene Ch'ng's insight:

As we move on into the future, we'll discover that everything can be modelled by agents as part of a complex system. 

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A New World Order is Emerging - InfoBarrel

A New World Order is Emerging - InfoBarrel | Information, Complexity, Computation | Scoop.it
A new world order is sweeping the earth. Networks, though still local, have evolved to be global. Our connections no longer stop at the border.
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What is complex systems science: Opportunities and insights. Yaneer Bar-Yam

Only 15 years ago, complex systems science had to justify its existence. Today it is taking the world by storm. Networks, big data, cascading crises, extreme events, the word "systems," and many other ideas are widely accepted and the basis for new advances and increasing the scope of science. What is this movement about, what changes are in store, and what are the opportunities for engagement? We will answer these questions, and others that you have, in this web presentation.

 

What is complex systems science: Opportunities and insights.

Yaneer Bar-Yam

Monday, December 17
12:00 to 12:30 PM


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Tim Williamson's comment, December 15, 2012 7:27 PM
Good read.
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Internet and Society – Social Theory in the Information Age

The study on Internet and  Society undertaken here  takes place within a  larger  framework that  has  during  the  last  years  been  labeled with  categories  like  Internet  research,  ICTs  and...

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lauryn burkhalter's comment, December 5, 2012 12:34 AM
This looks like a really interesting study. Thank you !
Alejandro Peñalosa C.'s comment, December 5, 2012 1:14 PM
You're wellcome!!
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Philosophy of Complex Systems

Philosophy of Complex Systems | Information, Complexity, Computation | Scoop.it

The domain of nonlinear dynamical systems and its mathematical underpinnings has been developing exponentially for a century, the last 35 years seeing an outpouring of new ideas and applications and a concomitant confluence with ideas of complex systems and their applications from irreversible thermodynamics. A few examples are in meteorology, ecological dynamics, and social and economic dynamics. These new ideas have profound implications for our understanding and practice in domains involving complexity, predictability and determinism, equilibrium, control, planning, individuality, responsibility and so on.

Our intention is to draw together in this volume, we believe for the first time, a comprehensive picture of the manifold philosophically interesting impacts of recent developments in understanding nonlinear systems and the unique aspects of their complexity. The book will focus specifically on the philosophical concepts, principles, judgments and problems distinctly raised by work in the domain of complex nonlinear dynamical systems, especially in recent years.

 

Philosophy of Complex Systems

Edited by Cliff Hooker


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Antifragile: Things That Gain from Disorder: Nassim Nicholas Taleb

Antifragile: Things That Gain from Disorder

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Nassim Nicholas Taleb, the bestselling author of The Black Swan and one of the foremost thinkers of our time, reveals how to thrive in an uncertain world.

Just as human bones get stronger when subjected to stress and tension, and rumors or riots intensify when someone tries to repress them, many things in life benefit from stress, disorder, volatility, and turmoil. What Taleb has identified and calls “antifragile” is that category of things that not only gain from chaos but need it in order to survive and flourish.

In The Black Swan, Taleb showed us that highly improbable and unpredictable events underlie almost everything about our world. In Antifragile, Taleb stands uncertainty on its head, making it desirable, even necessary, and proposes that things be built in an antifragile manner. The antifragile is beyond the resilient or robust. The resilient resists shocks and stays the same; the antifragile gets better and better.


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Walter Stickle's curator insight, December 14, 2012 10:14 AM

Despite the fact the the writing is deliberately provocative, carelessly dogmatic and typically lacking in rigour... the books central thesis is both highly important and almost completely lacking in our culture's worldview.  Read it!

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Japan Crop Circle Mystery Solved 2012 HD

According to the National Oceanic and Atmospheric Administration less than five percent of the world's oceans have been explored, meaning that 95% of what li...
Eugene Ch'ng's insight:

Stigmergy at work!

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European Conference on Complex Systems 2013

World Trade Center, Barcelona, 16-20 September 2013


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Complexity Digest's curator insight, December 23, 2012 8:16 AM

Follow on twitter @eccs13

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Cartels Are an Emergent Phenomenon, Say Complexity Theorists

Cartels Are an Emergent Phenomenon, Say Complexity Theorists | Information, Complexity, Computation | Scoop.it

“The price of gas is a puzzle. Monitor the average price in gas stations in a particular city and it will vary dramatically, sometimes in a matter of hours and often in ways that appear cyclical. 

 

Economist have long scratched their heads over this kind of pattern. One explanation is that this behaviour emerges when two competing companies change their pricing strategy at each stage by reacting to the other. The resulting behaviours are known as Edgeworth Price Cycles.

 

The problem is that gas station prices are not controlled by two competing players but many competing retailers. It’s easy to assume that the many-body problem produces similar patterns but nobody has been able to show this. 

 

Until now. Today Tiago Peixoto and Stefan Bornholdt, physicists at the University of Bremen in Germany, show how a more complicated model with many buyers and sellers reproduces this kind of behaviour. 

 

But it also goes further. Peixoto and Bornholdt say that when condition are right, cartel-like behaviour emerges naturally without collusion between sellers.


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What Will Come After Language?

What Will Come After Language? | Information, Complexity, Computation | Scoop.it
h+ Magazine is a new publication that covers technological, scientific, and cultural trends that are changing human beings in fundamental ways.
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The future language will be Psynese!

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12th International Conference of Sociocybernetics

The 2013 edition of the international RC51 meeting of Sociocybernetics will be held from 24th to 28th June at Centro Cultural Universitario” of the Universidad Autónoma de Yucatán, Mexico.

The conference title is “The sociocybernetics of social systems and social networks”.


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Boldly Going Beyond Mathematics

For one thing, complex systems do not easily lend themselves to analysis, the process of taking apart a system and examining its components individually. If taken apart, many complex systems lose precisely the character that makes them complex. The essence of these systems, then, seems to lie not in the nature of their components but in how the components interact—across different hierarchies, in synergistic and antagonistic manners. The agents within these systems are heterogeneous (think participants in a market economy or molecules within a cell), and their behavior is influenced by the type and quantity of other agents nearby. Such systems defy description with the traditional tool of theory builders: mathematics. Instead, they must be modeled by taking into account the rules of interaction, the natures of the agents, and the way the agents, rules, and ultimately whole systems came about. In his Signals and Boundaries: Building Blocks for Complex Adaptive Systems, John Holland proposes that computational modeling is the appropriate tool not only for describing but, fundamentally, for understanding such systems. In particular, he argues that this modeling approach is in no way inferior to a mathematical one. Rather, he advocates that the computational modeling of signal-boundary systems (which I will describe in more detail below) goes where mathematics cannot go while being no less rigorous, no less exact.

Boldly Going Beyond Mathematics
Christoph Adami
Science 14 December 2012:
Vol. 338 no. 6113 pp. 1421-1422
http://dx.doi.org/10.1126/science.1230587

Signals and Boundaries: Building Blocks for Complex Adaptive Systems
John H. Holland
http://tinyurl.com/cvk3t6u
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ComplexInsight's curator insight, January 5, 2013 8:50 AM

Good review of a great book.

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What can you do with a supercomputer? | ExtremeTech

What can you do with a supercomputer? | ExtremeTech | Information, Complexity, Computation | Scoop.it
In general, when ExtremeTech or another technology website discusses supercomputers, it's always in terms of speed -- what's rarely discussed, however, is the purpose of supercomputers.
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Well, I could definitely model massively multiagent systems with it!

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Complexity and the Limits of Revolution: What Will Happen to the Arab Spring? | NECSI

Complexity and the Limits of Revolution: What Will Happen to the Arab Spring? | NECSI | Information, Complexity, Computation | Scoop.it
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Introduction to Parallel Programming: Predicting Performance - Go Parallel

The video lecture offers definitions for the performance metrics speedup and efficiency. A fence painting example illustrates how to compute these metrics.
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TEDxZurich: Who Controls The World

It sounds paradoxical, but today it appears that we understand more about the universe than our society. We have created systems that have outgrown our capacity to genuinely understand and control them. Just think about the ongoing financial crisis. But recent advancements in the study of complex systems are able to offer new insights into the workings of many real-world systems.

 


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Internet and Society – Social Theory in the Information Age

The study on Internet and  Society undertaken here  takes place within a  larger  framework that  has  during  the  last  years  been  labeled with  categories  like  Internet  research,  ICTs  and...

Via Dr. Susan Bainbridge
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lauryn burkhalter's comment, December 5, 2012 12:34 AM
This looks like a really interesting study. Thank you !
Alejandro Peñalosa C.'s comment, December 5, 2012 1:14 PM
You're wellcome!!
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Complex social contagion makes networks more vulnerable to disease outbreaks

Social network analysis is now widely used to investigate the dynamics of infectious disease spread from person to person. Vaccination dramatically disrupts the disease transmission process on a contact network, and indeed, sufficiently high vaccination rates can disrupt the process to such an extent that disease transmission on the network is effectively halted. Here, we build on mounting evidence that health behaviors - such as vaccination, and refusal thereof - can spread through social networks through a process of complex contagion that requires social reinforcement. Using network simulations that model both the health behavior and the infectious disease spread, we find that under otherwise identical conditions, the process by which the health behavior spreads has a very strong effect on disease outbreak dynamics. This variability in dynamics results from differences in the topology within susceptible communities that arise during the health behavior spreading process, which in turn depends on the topology of the overall social network. Our findings point to the importance of health behavior spread in predicting and controlling disease outbreaks.

 

Complex social contagion makes networks more vulnerable to disease outbreaks

Ellsworth Campbell, Marcel Salathé

http://arxiv.org/abs/1211.0518


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