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Shock waves on complex networks

Shock waves on complex networks | Papers | Scoop.it

Power grids, road maps, and river streams are examples of infrastructural networks which are highly vulnerable to external perturbations. An abrupt local change of load (voltage, traffic density, or water level) might propagate in a cascading way and affect a significant fraction of the network. Almost discontinuous perturbations can be modeled by shock waves which can eventually interfere constructively and endanger the normal functionality of the infrastructure. We study their dynamics by solving the Burgers equation under random perturbations on several real and artificial directed graphs. Even for graphs with a narrow distribution of node properties (e.g., degree or betweenness), a steady state is reached exhibiting a heterogeneous load distribution, having a difference of one order of magnitude between the highest and average loads. Unexpectedly we find for the European power grid and for finite Watts-Strogatz networks a broad pronounced bimodal distribution for the loads. To identify the most vulnerable nodes, we introduce the concept of node-basin size, a purely topological property which we show to be strongly correlated to the average load of a node.


Shock waves on complex networks
• Enys Mones, Nuno A. M. Araújo, Tamás Vicsek & Hans J. Herrmann

Scientific Reports 4, Article number: 4949 http://dx.doi.org/10.1038/srep04949


Via Shaolin Tan
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Eli Levine's curator insight, May 20, 8:19 AM

Indeed, this is intuitive enough without the mathematics to back it up.  This could be mapped out and used for prioritizing the defense or attack of various points within the network, either in the digital or analog worlds.

 

Way cool science!

 

Think about it.

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Randomized Binary Consensus with Faulty Agents

This paper investigates self-organizing binary majority consensus disturbed by faulty nodes with random and persistent failure. We study consensus in ordered and random networks with noise, message loss and delays. Using computer simulations, we show that: (1) explicit randomization by noise, message loss and topology can increase robustness towards faulty nodes; (2) commonly-used faulty nodes with random failure inhibit consensus less than faulty nodes with persistent failure; and (3) in some cases, such randomly failing faulty nodes can even promote agreement.


Randomized Binary Consensus with Faulty Agents
Alexander Gogolev and Lucio Marcenaro

Entropy 2014, 16(5), 2820-2838; http://dx.doi.org/10.3390/e16052820

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A Fool to Do Your Dirty Work?

Anytime complexity increases through evolution, one must ask how selection at the lower level of organization (i.e., the individual cell) doesn't disrupt the integration at higher levels of organization (i.e., a multicellular organism) by favoring selfishness. There are some general evolutionary hypotheses that have been offered to explain why and how multicellularity and the division of labor between somatic and germline cells evolved, as well as the conditions under which these developments would be expected. Clearly, organisms with differentiated cells can experience many fitness advantages, such as the ability to grow larger and exploit novel resources. And along with these advantages come costs, such as the energy and materials that must be allocated towards growth and maintenance, rather than reproduction. However, there are more subtle, but no less important, constraints on an organism's ability to acquire resources, grow, metabolize, and reproduce that might also influence the evolution of cellular differentiation. (...)


Chase JM (2014) A Fool to Do Your Dirty Work? PLoS Biol 12(5): e1001859. http://dx.doi.org/10.1371/journal.pbio.1001859

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Eli Levine's curator insight, May 15, 10:09 AM

As an organism gets more complex, it seems that the cells become more simple, in and of themselves, and more interconnected to form the vibrant pattern of cells that form a multi-cellular organism.

 

Kind of like how, in a society where the division of labor took root, to eventually form the assembly line concept.  As society became more complex and diversified, it stands to reason that some larger, all guiding logic needs to pervade the social order, such that behavior is corrected according to thes social standards that are set within the given society (enter religion and/or government) to maintain the integrity of the overall whole that is the social organism.

 

Now, perhaps, it is time that all of these social superstructures: religion, government and business leaders, submit to the larger nature that is our natural world, such that we're actually living in harmony with the constantly evolving and dynamic nature, rather than next to or "over" it.  Survival is the name of the game and adaptability with an accurate sensor of reality is how you win it (bearing in mind, that we've all lost against the race against time and will only leave memory imprints behind when we're gone).  No sense in trying to achieve that which canont be achieved without killiing yourself and your population.

 

Think about it.

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The Emerging Science of Superspreaders (And How to Tell If You're One Of Them)

The Emerging Science of Superspreaders (And How to Tell If You're One Of Them) | Papers | Scoop.it
Nobody has figured out how to spot the most influential spreaders of information in a real-world network. Now that looks set to change with important implications, not least for the superspreaders themselves.


http://www.technologyreview.com/view/527271/the-emerging-science-of-superspreaders-and-how-to-tell-if-youre-one-of-them/

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Calculating Kolmogorov Complexity from the Output Frequency Distributions of Small Turing Machines

The evaluation of the complexity of finite sequences is key in many areas of science. For example, the notions of structure, simplicity and randomness are common currency in biological systems epitomized by a sequence of fundamental nature and utmost importance: the DNA. Nevertheless, researchers have for a long time avoided any practical use of the current accepted mathematical theory of randomness, mainly because it has been considered to be useless in practice [8]. Despite this belief, related notions such as lossless uncompressibility tests have proven relative success, in areas such as sequence pattern detection [21] and have motivated distance measures and classification methods [9] in several areas (see [19] for a survey), to mention but two examples among many others of even more practical use. The method presented in this paper aims to provide sound directions to explore the feasibility and stability of the evaluation of the complexity of strings by means different to that of lossless compressibility, particularly useful for short strings. The authors known of only two similar attempts to compute the uncomputable, one related to the estimation of a Chaitin Omega number [4], and of another seminal related measure of complexity, Bennett's Logical Depth [23], [27]. This paper provides an approximation to the output frequency distribution of all Turing machines with 5 states and 2 symbols which in turn allow us to apply a central theorem in the theory of algorithmic complexity based in the notion of algorithmic probability (also known as Solomonoff's theory of inductive inference) that relates frequency of production of a string and its Kolmogorov complexity hence providing, upon application of the theorem, numerical estimations of Kolmogorov complexity by a method different to lossless compression algorithms.


Soler-Toscano F, Zenil H, Delahaye J-P, Gauvrit N (2014) Calculating Kolmogorov Complexity from the Output Frequency Distributions of Small Turing Machines. PLoS ONE 9(5): e96223. http://dx.doi.org/10.1371/journal.pone.0096223

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Containing Epidemic Outbreaks by Message-Passing Techniques

Containing Epidemic Outbreaks by Message-Passing Techniques | Papers | Scoop.it

The problem of targeted network immunization can be defined as the one of finding a subset of nodes in a network to immunize or vaccinate in order to minimize a tradeoff between the cost of vaccination and the final (stationary) expected infection under a given epidemic model. Although computing the expected infection is a hard computational problem, simple and efficient mean-field approximations have been put forward in the literature in recent years. The optimization problem can be recast into a constrained one in which the constraints enforce local mean-field equations describing the average stationary state of the epidemic process. For a wide class of epidemic models, including the susceptible-infected-removed and the susceptible-infected-susceptible models, we define a message-passing approach to network immunization that allows us to study the statistical properties of epidemic outbreaks in the presence of immunized nodes as well as to find (nearly) optimal immunization sets for a given choice of parameters and costs. The algorithm scales linearly with the size of the graph, and it can be made efficient even on large networks. We compare its performance with topologically based heuristics, greedy methods, and simulated annealing on both random graphs and real-world networks.

 

http://dx.doi.org/10.1103/PhysRevX.4.021024
Containing Epidemic Outbreaks by Message-Passing Techniques
F. Altarelli, A. Braunstein, L. Dall’Asta, J. R. Wakeling, and R. Zecchina

Phys. Rev. X 4, 021024 – Published 8 May 2014

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A theoretical formalism for analyzing agent-based models

Following Holland, complex adaptive systems (CASs) are collections of interacting, autonomous, learning decision makers embedded in an interactive environment. Modeling CASs is challenging for a variety of reasons including the presence of heterogeneity, spatial relationships, nonlinearity, and, of course, adaptation. The challenges of modeling CASs can largely be overcome by using the individual-level focus of agent-based modeling. Agent-based modeling has been used successfully to model CASs in many disciplines. Many of these models were implemented using agent-based modeling software such as Swarm, Repast 3, Repast Simphony, Repast for High-Performance Computing, MASON, NetLogo, or StarLogo. All of these options use modular imperative architectures with factored agents, spaces, a scheduler, logs, and an interface. Many custom agent-based models also use this kind of architecture. This paper’s contribution is to introduce and apply a theoretical formalism for analyzing modular imperative agent-based models of CASs. This paper includes an analysis of three example models to show how the formalism is useful for predicting the execution time and space requirements for representations of common CASs.

(...)

This paper’s contribution is to introduce, analyze, and apply a theoretical formalism for proving findings about agent-based models with modular agent scheduler architectures. Given that this kind of modeling is both computationally optimal and a natural structural match for many modeling problems, it follows that it is the best modeling method for such problems.


A theoretical formalism for analyzing agent-based models
Michael J North

Complex Adaptive Systems Modeling 2014, 2:3  http://dx.doi.org/10.1186/2194-3206-2-3

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Modeling dynamics of attention in social media with user efficiency

Evolution of online social networks is driven by the need of their members to share and consume content, resulting in a complex interplay between individual activity and attention received from others. In a context of increasing information overload and limited resources, discovering which are the most successful behavioral patterns to attract attention is very important. To shed light on the matter, we look into the patterns of activity and popularity of users in the Yahoo Meme microblogging service. We observe that a combination of different type of social and content-producing activity is necessary to attract attention and the efficiency of users, namely the average attention received per piece of content published, for many users has a defined trend in its temporal footprint. The analysis of the user time series of efficiency shows different classes of users whose different activity patterns give insights on the type of behavior that pays off best in terms of attention gathering. In particular, sharing content with high spreading potential and then supporting the attention raised by it with social activity emerges as a frequent pattern for users gaining efficiency over time.


Modeling dynamics of attention in social media with user efficiency
Carmen Vaca Ruiz, Luca Maria Aiello and Alejandro Jaimes

EPJ Data Science 2014, 3:5  http://dx.doi.org/10.1140/epjds30

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How Community Feedback Shapes User Behavior

Social media systems rely on user feedback and rating mechanisms for personalization, ranking, and content filtering. However, when users evaluate content contributed by fellow users (e.g., by liking a post or voting on a comment), these evaluations create complex social feedback effects. This paper investigates how ratings on a piece of content affect its author's future behavior. By studying four large comment-based news communities, we find that negative feedback leads to significant behavioral changes that are detrimental to the community. Not only do authors of negatively-evaluated content contribute more, but also their future posts are of lower quality, and are perceived by the community as such. Moreover, these authors are more likely to subsequently evaluate their fellow users negatively, percolating these effects through the community. In contrast, positive feedback does not carry similar effects, and neither encourages rewarded authors to write more, nor improves the quality of their posts. Interestingly, the authors that receive no feedback are most likely to leave a community. Furthermore, a structural analysis of the voter network reveals that evaluations polarize the community the most when positive and negative votes are equally split.


How Community Feedback Shapes User Behavior
Justin Cheng, Cristian Danescu-Niculescu-Mizil, Jure Leskovec

http://arxiv.org/abs/1405.1429

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A Multi-Level Geographical Study of Italian Political Elections from Twitter Data

A Multi-Level Geographical Study of Italian Political Elections from Twitter Data | Papers | Scoop.it

In this paper we present an analysis of the behavior of Italian Twitter users during national political elections. We monitor the volumes of the tweets related to the leaders of the various political parties and we compare them to the elections results. Furthermore, we study the topics that are associated with the co-occurrence of two politicians in the same tweet. We cannot conclude, from a simple statistical analysis of tweet volume and their time evolution, that it is possible to precisely predict the election outcome (or at least not in our case of study that was characterized by a “too-close-to-call” scenario). On the other hand, we found that the volume of tweets and their change in time provide a very good proxy of the final results. We present this analysis both at a national level and at smaller levels, ranging from the regions composing the country to macro-areas (North, Center, South).

 

http://dx.doi.org/10.1371/journal.pone.0095809

Multi-Level Geographical Study of Italian Political Elections from Twitter Data

Caldarelli G, Chessa A, Pammolli F, Pompa G, Puliga M, et al.

PLoS ONE 9(5): e95809 (2014)

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Communicability reveals a transition to coordinated behavior in multiplex networks

Communicability reveals a transition to coordinated behavior in multiplex networks | Papers | Scoop.it

We analyze the flow of information in multiplex networks by means of the communicability function. First, we generalize this measure from its definition from simple graphs to multiplex networks. Then, we study its relevance for the analysis of real-world systems by studying a social multiplex where information flows using formal-informal channels and an air transportation system where the layers represent different air companies. Accordingly, the communicability, which is essential for the good performance of these complex systems, emerges at a systemic operation point in the multiplex where the performance of the layers operates in a coordinated way very differently from the state represented by a collection of unconnected networks.


Communicability reveals a transition to coordinated behavior in multiplex networks
Phys. Rev. E 89, 042819 – Published 30 April 2014
Ernesto Estrada and Jesús Gómez-Gardeñes

http://dx.doi.org/10.1103/PhysRevE.89.042819


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Geotagging One Hundred Million Twitter Accounts with Total Variation Minimization

Geographically annotated social media is extremely valuable for modern information retrieval. However, when researchers can only access publicly-visible data, one quickly finds that social media users rarely publish location information. In this work, we provide a method which can geolocate the overwhelming majority of active Twitter users, independent of their location sharing preferences, using only publicly-visible Twitter data.


Geotagging One Hundred Million Twitter Accounts with Total Variation Minimization
Ryan Compton, David Jurgens, David Allen

http://arxiv.org/abs/1404.7152


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Kinetics of wealth and the Pareto law

Kinetics of wealth and the Pareto law | Papers | Scoop.it

An important class of economic models involve agents whose wealth changes due to transactions with other agents. Several authors have pointed out an analogy with kinetic theory, which describes molecules whose momentum and energy change due to interactions with other molecules. We pursue this analogy and derive a Boltzmann equation for the time evolution of the wealth distribution of a population of agents for the so-called Yard-Sale Model of wealth exchange. We examine the solutions to this equation by a combination of analytical and numerical methods and investigate its long-time limit. We study an important limit of this equation for small transaction sizes and derive a partial integrodifferential equation governing the evolution of the wealth distribution in a closed economy. We then describe how this model can be extended to include features such as inflation, production, and taxation. In particular, we show that the model with taxation exhibits the basic features of the Pareto law, namely, a lower cutoff to the wealth density at small values of wealth, and approximate power-law behavior at large values of wealth.


Kinetics of wealth and the Pareto law
Phys. Rev. E 89, 042804 – Published 8 April 2014
Bruce M. Boghosian

http://dx.doi.org/10.1103/PhysRevE.89.042804


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Short-Term Forecasting of Taiwanese Earthquakes Using a Universal Model of Fusion-Fission Processes

Short-Term Forecasting of Taiwanese Earthquakes Using a Universal Model of Fusion-Fission Processes | Papers | Scoop.it

Predicting how large an earthquake can be, where and when it will strike remains an elusive goal in spite of the ever-increasing volume of data collected by earth scientists. In this paper, we introduce a universal model of fusion-fission processes that can be used to predict earthquakes starting from catalog data. We show how the equilibrium dynamics of this model very naturally explains the Gutenberg-Richter law. Using the high-resolution earthquake catalog of Taiwan between Jan 1994 and Feb 2009, we illustrate how out-of-equilibrium spatio-temporal signatures in the time interval between earthquakes and the integrated energy released by earthquakes can be used to reliably determine the times, magnitudes, and locations of large earthquakes, as well as the maximum numbers of large aftershocks that would follow.

 

http://dx.doi.org/10.1038/srep03624

Short-Term Forecasting of Taiwanese Earthquakes Using a Universal Model of Fusion-Fission Processes

Siew Ann Cheong, Teck Liang Tan, Chien-Chih Chen, Wu-Lung Chang, Zheng Liu, Lock Yue Chew, Peter M. A. Sloot & Neil F. Johnson

Scientific Reports 4, Article number: 3624

Complexity Digest's insight:

Earthquake prediction has proven to be elusive. Could this work make a breakthrough?

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Do We Need Asimov's Laws?

In recent years, roboticists have made rapid advances in the technologies that are bringing closer the kind of advanced robots that Asimov envisaged. Increasingly, robots and humans are working together on factory floors, driving cars, flying aircraft and even helping around the home.
And that raises an interesting question: do we need a set of Asimov-like laws to govern the behaviour of robots as they become more advanced?


http://www.technologyreview.com/view/527336/do-we-need-asimovs-laws/

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Eli Levine's curator insight, May 16, 6:16 PM

Well, I will say this: robots only are capable of doing what they're programmed or commanded to do.

 

It's not like these laws are actually followed by designers.  Were that the case, there would be no such thing as Predator drones (which are technically a violation of all laws of robotics).  We can destroy ourselves with machines, quite easily.  We can make overly effective instruments of destruction and eliminate the need for our presence in the world through automation.  However, we can also benefit from machines, especially in the worlds of policy making and implants, to make us more intelligent and accurate/effective processors of reality.  I would keep the consequences of ones' actions in mind when designing machines.  However, especially in our current state, there's no guarantee of that happening.

 

So, we've got a Russian roulette thing going on now, until we become more knowledgeable and aware of what works and how things work.  We can kill or hurt ourselves severely with the development of technology, as much as we can help and heal ourselves.

 

Let the experiments begin?  No choice, already begun.

 

Onward to the edge.

 

Think about it.

Gary Bamford's curator insight, May 17, 4:25 AM

Sign me up for the extra memory chip, current one seems to be struggling to keep up!

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How to Ask for a Favor: A Case Study on the Success of Altruistic Requests

Requests are at the core of many social media systems such as question & answer sites and online philanthropy communities. While the success of such requests is critical to the success of the community, the factors that lead community members to satisfy a request are largely unknown. Success of a request depends on factors like who is asking, how they are asking, when are they asking, and most critically what is being requested, ranging from small favors to substantial monetary donations. We present a case study of altruistic requests in an online community where all requests ask for the very same contribution and do not offer anything tangible in return, allowing us to disentangle what is requested from textual and social factors. Drawing from social psychology literature, we extract high-level social features from text that operationalize social relations between recipient and donor and demonstrate that these extracted relations are predictive of success. More specifically, we find that clearly communicating need through the narrative is essential and that that linguistic indications of gratitude, evidentiality, and generalized reciprocity, as well as high status of the asker further increase the likelihood of success. Building on this understanding, we develop a model that can predict the success of unseen requests, significantly improving over several baselines. We link these findings to research in psychology on helping behavior, providing a basis for further analysis of success in social media systems.


How to Ask for a Favor: A Case Study on the Success of Altruistic Requests
Tim Althoff, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky

http://arxiv.org/abs/1405.3282

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june holley's curator insight, May 19, 10:07 AM

Important information about micro processes that make networks work well!

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Guided Self-Organization in a Dynamic Embodied System Based on Attractor Selection Mechanism

Guided self-organization can be regarded as a paradigm proposed to understand how to guide a self-organizing system towards desirable behaviors, while maintaining its non-deterministic dynamics with emergent features. It is, however, not a trivial problem to guide the self-organizing behavior of physically embodied systems like robots, as the behavioral dynamics are results of interactions among their controller, mechanical dynamics of the body, and the environment. This paper presents a guided self-organization approach for dynamic robots based on a coupling between the system mechanical dynamics with an internal control structure known as the attractor selection mechanism. The mechanism enables the robot to gracefully shift between random and deterministic behaviors, represented by a number of attractors, depending on internally generated stochastic perturbation and sensory input. The robot used in this paper is a simulated curved beam hopping robot: a system with a variety of mechanical dynamics which depends on its actuation frequencies. Despite the simplicity of the approach, it will be shown how the approach regulates the probability of the robot to reach a goal through the interplay among the sensory input, the level of inherent stochastic perturbation, i.e., noise, and the mechanical dynamics.


Guided Self-Organization in a Dynamic Embodied System Based on Attractor Selection Mechanism
Surya G. Nurzaman , Xiaoxiang Yu, Yongjae Kim and Fumiya Iida

Entropy 2014, 16(5), 2592-2610

http://www.mdpi.com/1099-4300/16/5/2592

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Eli Levine's curator insight, May 14, 8:18 AM

This ties in with the concept of changing the software that runs on society's particular hardware.  Government is the control mechanism in a given society and it must obey the natural laws of the society in order to get the responses and effects that its members wish to have on the society.  This is similar to an airplane, in that the only way to get an airplane safely, reliably and consistently off the ground is to obey the natural laws of physics in the world that the airplane is also apart of.

 

It should be noted here that only benevolence, care, honesty, cost effectiveness and genuine action for the sake of the general public, however those are done, are the only ways for a government and its members to stay in power.  Underhanded techniques or the imposition of brute force will not work, especially in the context of an American society.  Such is how things work in our world.  And it's unfortunate that so many people who actually are holding political power in our society are so apparently clueless and unwilling to accept these principles in their daily courses of action.

 

Think about it.

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Dynamic pricing of network goods with boundedly rational consumers

We present a model of dynamic monopoly pricing for a good that displays network effects. In contrast with the standard notion of a rational-expectations equilibrium, we model consumers as boundedly rational and unable either to pay immediate attention to each price change or to make accurate forecasts of the adoption of the network good. Our analysis shows that the seller’s optimal price trajectory has the following structure: The price is low when the user base is below a target level, is high when the user base is above the target, and is set to keep the user base stationary once the target level has been attained. We show that this pricing policy is robust to a number of extensions, which include the product’s user base evolving over time and consumers basing their choices on a mixture of a myopic and a “stubborn” expectation of adoption. Our results differ significantly from those that would be predicted by a model based on rational-expectations equilibrium and are more consistent with the pricing of network goods observed in practice.


http://dx.doi.org/10.1073/pnas.1319543110

Dynamic pricing of network goods with boundedly rational consumers 

Roy Radnera, Ami Radunskayac, and Arun Sundararajan

PNAS Early Edition

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Beyond divisions [A synthetic biology special]

Since its debut in 2000, synthetic biology has seen considerable growth and now constitutes a vibrant research discipline that aims to apply engineering principles in the design and construction of complex biological systems. This Nature special charts the progress of the multidisciplinary field through reports, reviews and commentaries from Nature, Nature Methods and Nature Reviews Microbiology. Together, these explore the field’s potential and its challenges in developing clear goals, standards of practice and pathways to commercialization.


http://www.nature.com/news/specials/synbio-1.15137

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Want to Get Out Alive? Follow the Ants

Want to Get Out Alive? Follow the Ants | Papers | Scoop.it

“If you have an exit in the middle of the wall, you can imagine coming from the left side, the right side, and straight,” Shiwakoti says. These different streams of ants, or people, have to merge at the exit and take turns to pass. But people are impatient, and start pushing and shoving. Columns help structure the flow. “The column gives you some channels on the left and on the right, and this reduces the conflict at the exit.” The reason the corner exit is so efficient, Shiwakoti says, is because it has an intrinsic ability to structure the flow. “If the exit is in the corner, then people are probably only coming from left and right, so you have a more uniform flow.”


http://nautil.us/issue/13/symmetry/want-to-get-out-alive-follow-the-ants

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Percolation on sparse networks

We study percolation on networks, which is widely used as a model of the resilience of networked systems such as the Internet to attack or failure and as a simple model of the spread of disease over human contact networks. We reformulate percolation as a message passing process and use the resulting equations to show, among other things, that for sparse networks, which includes most networks observed in the real world, the percolation threshold is given by the inverse of the leading eigenvalue of the so-called non-backtracking matrix. Like most message passing calculations, our results are exact on networks that have few small loops but, as we show, they also provide bounds on the percolation behavior of networks that do contain loops.


Percolation on sparse networks
Brian Karrer, M. E. J. Newman, Lenka Zdeborová

http://arxiv.org/abs/1405.0483

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An exploration of social identity: The structure of the BBC news-sharing community on Twitter

Online social media influence the flow of news and other information, potentially altering collective social action while generating a large volume of data useful to researchers. Mapping these networks may make it possible to predict the course of social and political movements, technology adoption, and economic behavior. Here, we map the network formed by Twitter users sharing British Broadcasting Corporation (BBC) articles. The global audience of the BBC is primarily organized by language with the largest linguistic groups receiving news in English, Spanish, Russian, and Arabic. Members of the network primarily “follow” members sharing articles in the same language, and these audiences are primarily located in geographical regions where the languages are native. The one exception to this rule is a cluster interested in Middle East news which includes both Arabic and English speakers. We further analyze English-speaking users, which differentiate themselves into four clusters: one interested in sports, two interested in United Kingdom (UK) news—with word usage suggesting this reflects political polarization into Conservative and Labour party leanings—and a fourth group that is the English speaking part of the group interested in Middle East news. Unlike the previously studied New York Times news sharing network the largest scale structure of the BBC network does not include a densely connected group of globally interested and globally distributed users. The political polarization is similar to what was found for liberal and conservative groups in the New York Times study. The observation of a primary organization of the BBC audience around languages is consistent with the BBC's unique role in history as an alternative source of local news in regions outside the UK where high quality uncensored news was not available.


An exploration of social identity: The structure of the BBC news-sharing community on Twitter
Julius Adebayo, Tiziana Musso, Kawandeep Virdee, Casey Friedman and Yaneer Bar-Yam

Complexity
Volume 19, Issue 5, pages 55–63, May/June 2014

http://dx.doi.org/10.1002/cplx.21490

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Measuring Large-Scale Social Networks with High Resolution

Measuring Large-Scale Social Networks with High Resolution | Papers | Scoop.it

This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years—the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1 000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection.

 

Measuring Large-Scale Social Networks with High Resolution

Stopczynski A, Sekara V, Sapiezynski P, et al.

PLoS ONE 9(4): e95978 (2014)

http://dx.doi.org/10.1371/journal.pone.0095978

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Universal bursty behaviour in human violent conflicts

Universal bursty behaviour in human violent conflicts | Papers | Scoop.it
Understanding the mechanisms and processes underlying the dynamics of collective violence is of considerable current interest. Recent studies indicated the presence of robust patterns characterizing the size and timing of violent events in human conflicts. Since the size and timing of violent events arises as the result of a dynamical process, we explore the possibility of unifying these observations. By analyzing available catalogs on violent events in Iraq (2003-2005), Afghanistan (2008-2010) and Northern Ireland (1969-2001), we show that the inter-event time distributions (calculated for a range of minimum sizes) obeys approximately a simple scaling law which holds for more than three orders of magnitude. This robust pattern suggests a hierarchical organization in size and time providing a unified picture of the dynamics of violent conflicts.


Universal bursty behaviour in human violent conflicts
• S. Picoli, M. del Castillo-Mussot, H. V. Ribeiro, E. K. Lenzi & R. S. Mendes

Scientific Reports 4, Article number: 4773 http://dx.doi.org/10.1038/srep04773

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Together we stand, Together we fall, Together we win: Dynamic Team Formation in Massive Open Online Courses

Massive Open Online Courses (MOOCs) offer a new scalable paradigm for e-learning by providing students with global exposure and opportunities for connecting and interacting with millions of people all around the world. Very often, students work as teams to effectively accomplish course related tasks. However, due to lack of face to face interaction, it becomes difficult for MOOC students to collaborate. Additionally, the instructor also faces challenges in manually organizing students into teams because students flock to these MOOCs in huge numbers. Thus, the proposed research is aimed at developing a robust methodology for dynamic team formation in MOOCs, the theoretical framework for which is grounded at the confluence of organizational team theory, social network analysis and machine learning. A prerequisite for such an undertaking is that we understand the fact that, each and every informal tie established among students offers the opportunities to influence and be influenced. Therefore, we aim to extract value from the inherent connectedness of students in the MOOC. These connections carry with them radical implications for the way students understand each other in the networked learning community. Our approach will enable course instructors to automatically group students in teams that have fairly balanced social connections with their peers, well defined in terms of appropriately selected qualitative and quantitative network metrics.


Together we stand, Together we fall, Together we win: Dynamic Team Formation in Massive Open Online Courses
Tanmay Sinha

http://arxiv.org/abs/1404.5521

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