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Researchers have developed the first global model that analyses the routes taken by marine invasive species.
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# Information, Complexity, Computation

All things complex
Curated by Eugene Ch'ng
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## Financial Brownian particle in the layered order-book fluid and fluctuation-dissipation relations

Eugene Ch'ng's insight:

We introduce a novel description of the dynamics of the order book of financial markets as that of an effective colloidal Brownian particle embedded in fluid particles. The analysis of a comprehensive market data enables us to identify all motions of the fluid particles. Correlations between the motions of the Brownian particle and its surrounding fluid particles reflect specific layering interactions; in the inner-layer, the correlation is strong and with short memory while, in the outer-layer, it is weaker and with long memory. By interpreting and estimating the contribution from the outer-layer as a drag resistance, we demonstrate the validity of the fluctuation-dissipation relation (FDR) in this non-material Brownian motion process.

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## Damage spreading in spatial and small-world random Boolean networks

The study of the response of complex dynamical social, biological, or technological networks to external perturbations has numerous applications. Random Boolean networks (RBNs) are commonly used as a simple generic model for certain dynamics of complex systems. Traditionally, RBNs are interconnected randomly and without considering any spatial extension and arrangement of the links and nodes. However, most real-world networks are spatially extended and arranged with regular, power-law, small-world, or other nonrandom connections. Here we explore the RBN network topology between extreme local connections, random small-world, and pure random networks, and study the damage spreading with small perturbations. We find that spatially local connections change the scaling of the Hamming distance at very low connectivities ($\bar{K} << 1$) and that the critical connectivity of stability $\bar{K}$ changes compared to random networks. At higher $\bar{K}$, this scaling remains unchanged. We also show that the Hamming distance of spatially local networks scales with a power law as the system size $N$ increases, but with a different exponent for local and small-world networks. The scaling arguments for small-world networks are obtained with respect to the system sizes and strength of spatially local connections. We further investigate the wiring cost of the networks. From an engineering perspective, our new findings provide the key design trade-offs between damage spreading (robustness), the network's wiring cost, and the network's communication characteristics.

Qiming Lu and Christof Teuscher
Damage spreading in spatial and small-world random Boolean networks
Phys. Rev. E 89, 022806 (2014)

http://pre.aps.org/abstract/PRE/v89/i2/e022806

Via Complexity Digest
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## The strength of ‘weak signals’

As information thunders through the digital economy, it’s easy to miss valuable “weak signals” often hidden amid the noise. Arising primarily from social media, they represent snippets—not streams—of information and can help companies to figure out what customers want and to spot looming industry and market disruptions before competitors do. Sometimes, companies notice them during data-analytics number-crunching exercises. Or employees who apply methods more akin to art than to science might spot them and then do some further number crunching to test anomalies they’re seeing or hypotheses the signals suggest. In any case, companies are just beginning to recognize and capture their value. Here are a few principles that companies can follow to grasp and harness the power of weak signals.

Via Complexity Digest
Eli Levine's curator insight,

The same can be said for governing, although the end goal is, when it's actually working for the sake of the governing, how to better serve people according to their needs and expressed desires.  The reward for good governance is continued time in office.  The way you actually get to that end is through a combination of listening for NEEDS (which aren't the same as wants) within the general public and then actively teasing those needs out so that you can understand them.

It's a pro-active dialogue, especially on the part of the governing, if it is being done in a way that is actually beneficial for the governing and the governed alike.  The former depends on the latter more than the latter depends on the former, because it is the governed which gives authority to the governing, while the governed can exist (if sub-optimally) without the governing group's present.  It doesn't even matter which specific group is in power, since they're all going to be bound to do the same basic stuff in the same basic ways, if they're going to produce optimal results for themselves and other people living in the society as a whole.  The only question that matters is "how well does the present governing group do at governing?"  Society is constantly open to shopping for other options; constantly playing the field if things become sub-optimal for society in some way, shape or form.

That is why a good government is proactive when working with its citizens and listening for these "weak signals", because those are what reveals the subtle workings of the group's psychology and what the group actually is needing/wanting versus what they explicitly express.

 Rescooped by Eugene Ch'ng from CxAnnouncements

## Guided Self-Organisation

Typically, self-organisation (SO) is defined as the evolution of a system into an organised form in the absence of external pressures. SO within a system brings about several attractive properties, in particular, robustness, adaptability and scalability. In the face of perturbations caused by adverse external factors or internal component failures, a robust self-organising system continues to function. Moreover, an adaptive system may re-configure when required, degrading in performance “gracefully” rather than catastrophically. In certain circumstances, a system may need to be extended with new components and/or new connections among existing modules — without SO such scaling must be preoptimised in advance, overloading the traditional design process.
In general, SO is a not a force that can be applied very naturally during a design process. In fact, one may argue that the notions of design and SO are contradictory: the former approach often assumes a methodical step-by-step planning process with predictable outcomes, while the latter involves non-deterministic spontaneous dynamics with emergent features. Thus, the main challenge faced by designers of self-organising systems is how to achieve and control the desired dynamics. Erring on the one side may result in over-engineering the system, completely eliminating emergent patterns and suppressing an increase in internal organisation with outside influence. Strongly favouring the other side may leave too much non-determinism in the system’s behaviour, making its verification and validation almost impossible. The balance between design and SO is the main theme of guided self-organisation (GSO). In short, GSO combines both task-independent objectives (e.g., information-theoretic and graph-theoretic utility functions) with task-dependent constraints.

http://guided-self.org

Via Complexity Digest
Liz Rykert's curator insight,

Love the paradox in this. Worth digging into.

Eli Levine's curator insight,

Indeed, you must obey the laws of society and those of economics, environmental science and psychology in order to govern a world.

The simple rules are already in place.  The question is how do we conform to those rules so that we realize the most optimal social function for everybody?

This is where lawyering and traditional politiking takes a back seat, and the technical world of governing begins.

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## Crowd-sourcing: Strength in numbers

Researchers are finding that online, crowd-sourced collaboration can speed up their work — if they choose the right problem.
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## Predicting Crowd Behavior with Big Public Data

With public information becoming widely accessible and shared on today's web, greater insights are possible into crowd actions by citizens and non-state actors such as large protests and cyber activism. We present efforts to predict the occurrence, specific timeframe, and location of such actions before they occur based on public data collected from over 300,000 open content web sources in 7 languages, from all over the world, ranging from mainstream news to government publications to blogs and social media. Using natural language processing, event information is extracted from content such as type of event, what entities are involved and in what role, sentiment and tone, and the occurrence time range of the event discussed. Statements made on Twitter about a future date from the time of posting prove particularly indicative. We consider in particular the case of the 2013 Egyptian coup d'etat. The study validates and quantifies the common intuition that data on social media (beyond mainstream news sources) are able to predict major events.

Predicting Crowd Behavior with Big Public Data
Nathan Kallus

http://arxiv.org/abs/1402.2308

Via Complexity Digest
António F Fonseca's curator insight,

Its becoming standard practice.

 Rescooped by Eugene Ch'ng from Non-Equilibrium Social Science

## SFI: notes for the history of Complex Systems Science

This is the first in a series of articles recounting the history of the Santa Fe Institute drawn from primary and, in a few cases, secondary sources.

By John German

In George Cowan's telling, the notion for a Santa Fe Institute began to form in the summer of 1956. He had been invited to the Aspen Institute, where prominent intellectuals from the arts, science, and culture gathered for free-form philosophical exchanges. He had just participated as the lone scientist in a discussion of literature. (...)

Via NESS
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 Rescooped by Eugene Ch'ng from Non-Equilibrium Social Science

## SocInfo 2014 | 6th international conference on Social Informatics

We are delighted to welcome the 6th International Conference on Social Informatics (SocInfo 2014) to Barcelona, Spain, from November 10th to November 13th.SocInfo is an interdisciplinary venue for researchers from Computer Science, Informatics, Social Sciences and Management Sciences to share ideas and opinions, and present original research work on studying the interplay between socially-centric platforms and social phenomena. The ultimate goal of Social Informatics is to create better understanding of socially-centric platforms not just as a technology, but also as a set of social phenomena. To that end, we are inviting interdisciplinary papers, on applying information technology in the study of social phenomena, on applying social concepts in the design of information systems, on applying methods from the social sciences in the study of social computing and information systems, on applying computational algorithms to facilitate the study of social systems and human social dynamics, and on designing information and communication technologies that consider social context.

http://socinfo2014.org

Via Complexity Digest, NESS
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## Video Reveals the Molecular Basis of Memory | Big Think TV | Big Think

A major advance in the use of microscopes for scientific investigation allows scientists to watch the brain create memories.
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## Chaos theory as the answer to limited spectrum? - Academia — Innovating for society

Ken Umeno, Professor at the Department of Applied Mathematics and Physics, Graduate School of Informatics, Kyoto University, Japan and Minghui Kao, Ch
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## Epidemics on social networks

Since its first formulations almost a century ago, mathematical models for disease spreading contributed to understand, evaluate and control the epidemic processes.They promoted a dramatic change in how epidemiologists thought of the propagation of infectious diseases.In the last decade, when the traditional epidemiological models seemed to be exhausted, new types of models were developed.These new models incorporated concepts from graph theory to describe and model the underlying social structure.Many of these works merely produced a more detailed extension of the previous results, but some others triggered a completely new paradigm in the mathematical study of epidemic processes. In this review, we will introduce the basic concepts of epidemiology, epidemic modeling and networks, to finally provide a brief description of the most relevant results in the field.

Epidemics on social networks
Marcelo N. Kuperman

http://arxiv.org/abs/1312.3838

Via Complexity Digest
António F Fonseca's curator insight,

A good review about epidemic models in social networks, SIS, SIR, etc ...

Marco Valli's curator insight,

Basics of SIS/SIR models of spreading epidemics, and their relations to social networks.

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## Interdisciplinary Marriage | Education Recoded | Big Think

Guest post by Kevin Flora   (Cross post from kevinflora.com)
Think as if there isn't a box, not just "outside the box".  Embrace change and accept your responsibility as a professional within the changing economy and world we live in.
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## Report calls on NHS to consistently use simulation software ahead of big decisions

The NHS could be run more effectively if senior decision makers used simulation software to test the outcome of different approaches before rolling them out, according to a report out today.
ComplexInsight's curator insight,

As someone who believes most many of societies bigger decisions would benefit from better simulations - the report makes for an interesting read. Simulation is going to grow in importance in many areas - as data analytics enable us to consider impact landscapes. Using large scale data analysis to drive simulations we can begin to use simulation as a means of possibility search (something engineering routinely does now) on a broader canvas.

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## Twitter 'big data' can be used to monitor HIV, drug-related behavior

Real-time social media like Twitter could be used to track HIV incidence and drug-related behaviors with the aim of detecting and potentially preventing outbreaks. The study suggests it may be possible to predict sexual risk and drug use behaviors by monitoring tweets, mapping where those messages come from and linking them with data on the geographical distribution of HIV cases. The use of various drugs had been associated in previous studies with HIV sexual risk behaviors and transmission of infectious disease.
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## How to Save Human Lives with Complexity Science

Eugene Ch'ng's insight:
We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are not effective and sufficient to contain them. The failure of many conventional approaches results from their neglection of feedback loops, instabilities and/or cascade effects, due to which equilibrium models do often not provide a good picture of the actual system behavior. However, the complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be understood by means of complexity science, which enables one to address the aforementioned problems more successfully. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.

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## The Relative Ineffectiveness of Criminal Network Disruption

Researchers, policymakers and law enforcement agencies across the globe struggle to find effective strategies to control criminal networks. The effectiveness of disruption strategies is known to depend on both network topology and network resilience. However, as these criminal networks operate in secrecy, data-driven knowledge concerning the effectiveness of different criminal network disruption strategies is very limited. By combining computational modeling and social network analysis with unique criminal network intelligence data from the Dutch Police, we discovered, in contrast to common belief, that criminal networks might even become ‘stronger’, after targeted attacks. On the other hand increased efficiency within criminal networks decreases its internal security, thus offering opportunities for law enforcement agencies to target these networks more deliberately. Our results emphasize the importance of criminal network interventions at an early stage, before the network gets a chance to (re-)organize to maximum resilience. In the end disruption strategies force criminal networks to become more exposed, which causes successful network disruption to become a long-term effort.

The Relative Ineffectiveness of Criminal Network Disruption
Paul A. C. Duijn, Victor Kashirin & Peter M. A. Sloot

Scientific Reports 4, Article number: 4238 http://dx.doi.org/10.1038/srep04238 ;

Via Complexity Digest
Eli Levine's curator insight,

My only critique of this, is that even by successfully disrupting the social networks, you will ont get rid of the foundations of crime within a society.

Greed, lust, violence, all of these things come from the brain and can be seen as mental health problems, rather than necessarily just societal problems.  I think we've got to begin ori sorting th the convected and post conicted crowd, such tht we can understand how their brains work and then, how to help heal them, such that we eliminate criminality and crime inspited lifestyles.  I understand there are dozens of easy ways to be opposed to this and that there are dozes more ways th work (especially here, in america, where we are soc focused on our small "selves" to forget that there is a much much much much larger world out thre, and that of ourselves as well.  We are connected to everyone and everything.  That's science.  To deny that it is otherwise is to invite delusion and hallucinations about reality and to invite other problems into your life and the rest of ours for your deliberate ignorance and unwillingness to escape to where reality simply is unoffensive and not politically motivated other than to help other people.

Therefore, let's overcome this monkey need to punish people for crimes they really didn't have much say in (thankst o the primacy of the brain) and start doing some research on these people (even though they should be confined from the rest of the population until treatments and diagnoses have been developed and concluded upon).

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## Crime rates could rise as climate change bites - environment - 28 February 2014 - New Scientist

As temperatures soar, so do crime rates – suggesting climate change will lead to millions of extra offences in the coming decades
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 Rescooped by Eugene Ch'ng from Papers

## Information Evolution in Social Networks

Social networks readily transmit information, albeit with less than perfect fidelity. We present a large-scale measurement of this imperfect information copying mechanism by examining the dissemination and evolution of thousands of memes, collectively replicated hundreds of millions of times in the online social network Facebook. The information undergoes an evolutionary process that exhibits several regularities. A meme's mutation rate characterizes the population distribution of its variants, in accordance with the Yule process. Variants further apart in the diffusion cascade have greater edit distance, as would be expected in an iterative, imperfect replication process. Some text sequences can confer a replicative advantage; these sequences are abundant and transfer "laterally" between different memes. Subpopulations of the social network can preferentially transmit a specific variant of a meme if the variant matches their beliefs or culture. Understanding the mechanism driving change in diffusing information has important implications for how we interpret and harness the information that reaches us through our social networks.

Information Evolution in Social Networks

http://arxiv.org/abs/1402.6792

Via Complexity Digest
António F Fonseca's curator insight,

Memes are the information science counterpath of particles to physics.

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## The Math That Predicted the Revolutions Sweeping the Globe Right Now

The complex systems theorists who predicted the Arab Spring built a model that predicted the unrest in Ukraine, Venezuela, and Thailand too.
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 Rescooped by Eugene Ch'ng from Non-Equilibrium Social Science

## Simulating the past to understand human history: satellite in 10th conference of the European Social Simulation Association (ESSA)

SIMULATING THE PAST TO UNDERSTAND HUMAN HISTORY

The conference is organized with the contribution of the SimulPast project(www.simulpast.es), a 5-year exploratory research project funded by the SpanishGovernment (MICINN CSD2010-00034) that aims at developing an innovative andinterdisciplinary methodological framework to model and simulate ancient societies andtheir relationship with environmental transformations. To achieve these aims, SimulPastintegrates knowledge from diverse fields covering humanities, social, computationaland ecological sciences within a national and international network.

The conference intention is to showcase the result of the SimulPast project together withcurrent international research on the methodological and theoretical aspects of computersimulation in archaeological and historical contexts. The conference will bring togetherscholars from different disciplinary backgrounds (history, ecology, archaeology,anthropology, sociology, computer science and complex systems) in order to promotedeeper understanding and collaboration in the study of past human behavior and history

Via NESS
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 Rescooped by Eugene Ch'ng from Non-Equilibrium Social Science

## 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...

Via Lorien Pratt, António F Fonseca, NESS
Lorien Pratt's curator insight,

This is a great introduction to the idea of emergent behavior from complex systems.  Many people don't realize that if individuals have very simple behaviors, there can be very complex behaviors when those individuals act in a group.  Understanding these emergent patterns is critical for good decision making, because you need to know how the decision you make will set other elements in the system in motion.  More and more, our social, economic, political, climate, and other realities have this characteristic.   This video focuses on agent-base complex systems, such flocks of birds, schools of fish, or even nanobot swarms to cure cancer.

António F Fonseca's curator insight,

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

Liz Rykert's curator insight,

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

 Scooped by Eugene Ch'ng

## Biology's 'dark matter' hints at fourth domain of life - life - 18 March 2011 - New Scientist

Over 99 per cent of organisms remain unknown to science – so could some of them sit outside the classic three domains of cellular life?
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Facebook's a disease and the cure's coming
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## Scientists glue sensors to 5,000 bees to study behaviour - Telegraph

Researchers have attached tiny sensors to thousands of bees as part of an experiment to better understand their behaviour
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