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Complex World
Cutting Edge Research about Complex Systems
Curated by Claudia Mihai
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Using Chaos Theory to Predict and Prevent Catastrophic 'Dragon King' Events

Using Chaos Theory to Predict and Prevent Catastrophic 'Dragon King' Events | Complex World | Scoop.it

Stop a stock trade and avoid a catastrophic global financial crash. Seal a microscopic crack and prevent a rocket explosion. Push a button to avert a citywide blackout.

Though such situations are mostly fantasies, a new analysis suggests that certain types of extreme events occurring in complex systems – known as dragon king events – can be predicted and prevented.

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Ali Anani's curator insight, November 9, 2013 3:54 AM

Can we control  the uncontrollable? 

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Study: neuroscientists develop equation for predicting future disasters

Study: neuroscientists develop equation for predicting future disasters | Complex World | Scoop.it
A team of neuroscientists has published a paper claiming it has developed a mathematical calculation that could potentially predict the tipping point of any massive event -- from a market crash to a brain seizure...
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Impact of Social Punishment on Cooperative Behavior in Complex Networks

Impact of Social Punishment on Cooperative Behavior in Complex Networks | Complex World | Scoop.it

Abstract: Social punishment is a mechanism by which cooperative individuals spend part of their resources to penalize defectors. In this paper, we study the evolution of cooperation in 2-person evolutionary games on networks when a mechanism for social punishment is introduced. Specifically, we introduce a new kind of role, punisher, which is aimed at reducing the earnings of defectors by applying to them a social fee. Results from numerical simulations show that different equilibria allowing the three strategies to coexist are possible as well as that social punishment further enhance the robustness of cooperation. Our results are confirmed for different network topologies and two evolutionary games. In addition, we analyze the microscopic mechanisms that give rise to the observed macroscopic behaviors in both homogeneous and heterogeneous networks. Our conclusions might provide additional insights for understanding the roots of cooperation in social systems.

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Now Facebook Can See Inside Your Heart, Too

Now Facebook Can See Inside Your Heart, Too | Complex World | Scoop.it

Facebook scientists figure out how to identify your romantic partner or best friend from among your connections.

Each day brings fresh confirmation that giving away any information means you’re giving all of it away, thanks to algorithms that crunch your language use, purchasing habits, friend structure, and other bits of information.

Now “big data” can see inside your heart.

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Cosmological networks

Cosmological networks | Complex World | Scoop.it
Networks often represent systems that do not have a long history of studies in traditional fields of physics, albeit there are some notable exceptions such as energy landscapes and quantum gravity. Here we consider networks that naturally arise in cosmology. Nodes in these networks are stationary observers uniformly distributed in an expanding open FLRW universe with any scale factor, and two observers are connected if one can causally influence the other. We show that these networks are growing Lorentz-invariant graphs with power-law distributions of node degrees. New links in these networks not only connect new nodes to existing ones, but also appear at a certain rate between existing nodes, as they do in many complex networks.
  
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Exploring Scientists' Working Timetable

Exploring Scientists' Working Timetable | Complex World | Scoop.it

In our previous study (Wang et al., 2012), we analyzed scientists' working timetable of 3 countries, using realtime downloading data of scientific literatures. In this paper, we make a through analysis about global scientists' working habits. Top 30 countries/territories from Europe, Asia, Australia, North America, Latin America and Africa are selected as representatives and analyzed in detail. Regional differences for scientists' working habits exists in different countries. Besides different working cultures, social factors could affect scientists' research activities and working patterns. Nevertheless, a common conclusion is that scientists today are often working overtime. Although scientists may feel engaged and fulfilled about their hard working, working too much still warns us to reconsider the work - life balance.

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The Decline of Wikipedia: Even As More People Than Ever Rely on It, Fewer People Create It

The Decline of Wikipedia: Even As More People Than Ever Rely on It, Fewer People Create It | Complex World | Scoop.it
The community that built the largest encyclopedia in history is shrinking, even as more people and Internet services depend on it than ever. Can it be revived, or is this the end of the Web’s idealistic era?
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The dynamics of correlated novelties

The dynamics of correlated novelties | Complex World | Scoop.it

One new thing often leads to another. Such correlated novelties are a familiar part of daily life. They are also thought to be fundamental to the evolution of biological systems, human society, and technology. By opening new possibilities, one novelty can pave the way for others in a process that Kauffman has called "expanding the adjacent possible". The dynamics of correlated novelties, however, have yet to be quantified empirically or modeled mathematically. Here we propose a simple mathematical model that mimics the process of exploring a physical, biological or conceptual space that enlarges whenever a novelty occurs. The model, a generalization of Polya's urn, predicts statistical laws for the rate at which novelties happen (analogous to Heaps' law) and for the probability distribution on the space explored (analogous to Zipf's law), as well as signatures of the hypothesized process by which one novelty sets the stage for another. We test these predictions on four data sets of human activity: the edit events of Wikipedia pages, the emergence of tags in annotation systems, the sequence of words in texts, and listening to new songs in online music catalogues. By quantifying the dynamics of correlated novelties, our results provide a starting point for a deeper understanding of the ever-expanding adjacent possible and its role in biological, linguistic, cultural, and technological evolution.

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Brown Bears Fighting, Playing & Scratching in Transylvanian Woods

Brown Bears Fighting, Playing & Scratching in Transylvanian Woods | Complex World | Scoop.it

Victoria Hillman is a National Geographic Explorer and Research Director for the Transylvanian Wildlife Project overseeing research on carnivores and biodiversity of Europe’s last great wilderness. Follow the expedition here on Explorers Journal through updates from the team.

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Trouble at the lab

Trouble at the lab | Complex World | Scoop.it

“I SEE a train wreck looming,” warned Daniel Kahneman, an eminent psychologist, in an open letter last year. The premonition concerned research on a phenomenon known as “priming”. Priming studies suggest that decisions can be influenced by apparently irrelevant actions or events that took place just before the cusp of choice. They have been a boom area in psychology over the past decade, and some of their insights have already made it out of the lab and into the toolkits of policy wonks keen on “nudging” the populace.

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The Anatomy of a Scientific Rumor

The Anatomy of a Scientific Rumor | Complex World | Scoop.it

Abstract: The announcement of the discovery of a Higgs boson-like particle at CERN will be remembered as one of the milestones of the scientific endeavor of the 21st century. In this paper we present a study of information spreading processes on Twitter before, during and after the announcement of the discovery of a new particle with the features of the elusive Higgs boson on 4th July 2012. We report evidence for non-trivial spatio-temporal patterns in user activities at individual and global level, such as tweeting, re-tweeting and replying to existing tweets. We provide a possible explanation for the observed time-varying dynamics of user activities during the spreading of this scientific “rumor”. We model the information spreading in the corresponding network of individuals who posted a tweet related to the Higgs boson discovery. Finally, we show that we are able to reproduce the global behavior of about 500,000 individuals with remarkable accuracy.

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Community detection: effective evaluation on large social networks

Community detection: effective evaluation on large social networks | Complex World | Scoop.it

Abstract: While many recently proposed methods aim to detect network communities in large datasets, such as those generated by social media and telecommunications services, most evaluation (i.e. benchmarking) of this research is based on small, hand-curated datasets. We argue that these two types of networks differ so significantly that, by evaluating algorithms solely on the smaller networks, we know little about how well they perform on the larger datasets. Recent work addresses this problem by introducing social network datasets annotated with meta-data that is believed to approximately indicate a ‘ground truth’ set of network communities. While such efforts are a step in the right direction, we find this meta-data problematic for two reasons. First, in practice, the groups contained in such meta-data may only be a subset of a network's communities. Second, while it is often reasonable to assume that meta-data is related to network communities in some way, we must be cautious about assuming that these groups correspond closely to network communities. Here, we consider these difficulties and propose an evaluation scheme based on a classification task that is tailored to deal with them.

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Eric L Berlow's curator insight, October 17, 2013 11:29 AM

Interesting evaluation of community detection algorithms in large networks.  Most have only been validated for small, hand-curated networks.

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Tweets Have Become Shorter Since 2009

Tweets Have Become Shorter Since 2009 | Complex World | Scoop.it
The length of the messages we send on Twitter is getting shorter, raising important questions about how the social messaging service is changing the way we communicate, say researchers
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On the Predictability of Future Impact in Science

On the Predictability of Future Impact in Science | Complex World | Scoop.it

Correctly assessing a scientist's past research impact and potential for future impact is key in recruitment decisions and other evaluation processes. While a candidate's future impact is the main concern for these decisions, most measures only quantify the impact of previous work. Recently, it has been argued that linear regression models are capable of predicting a scientist's future impact. By applying that future impact model to 762 careers drawn from three disciplines: physics, biology, and mathematics, we identify a number of subtle, but critical, flaws in current models. Specifically, cumulative non-decreasing measures like the h-index contain intrinsic autocorrelation, resulting in significant overestimation of their “predictive power”. Moreover, the predictive power of these models depend heavily upon scientists' career age, producing least accurate estimates for young researchers. Our results place in doubt the suitability of such models, and indicate further investigation is required before they can be used in recruiting decisions.

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Forget the needle, consider the haystack: Uncovering hidden structures in massive data collections

Forget the needle, consider the haystack: Uncovering hidden structures in massive data collections | Complex World | Scoop.it

Using a mathematical method that calculates the likelihood of a pattern repeating throughout a subset of data, the researchers have been able to cut dramatically the time needed to find patterns in large collections of information such as social networks. The tool allows researchers to identify quickly the connections between seemingly disparate groups such as theoretical physicists who study intermolecular forces and astrophysicists researching black holes.

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Atypical Combinations and Scientific Impact

Atypical Combinations and Scientific Impact | Complex World | Scoop.it

Novelty is an essential feature of creative ideas, yet the building blocks of new ideas are often embodied in existing knowledge. From this perspective, balancing atypical knowledge with conventional knowledge may be critical to the link between innovativeness and impact. Our analysis of 17.9 million papers spanning all scientific fields suggests that science follows a nearly universal pattern: The highest-impact science is primarily grounded in exceptionally conventional combinations of prior work yet simultaneously features an intrusion of unusual combinations. Papers of this type were twice as likely to be highly cited works. Novel combinations of prior work are rare, yet teams are 37.7% more likely than solo authors to insert novel combinations into familiar knowledge domains.

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Hierarchical block structures and high-resolution model selection in large networks

Hierarchical block structures and high-resolution model selection in large networks | Complex World | Scoop.it

Discovering the large-scale topological features in empirical networks is a crucial tool in understanding how complex systems function. However most existing methods used to obtain the modular structure of networks suffer from serious problems, such as the resolution limit on the size of communities, where smaller but well-defined clusters are not detectable when the network becomes large. This phenomenon occurs for the very popular approach of modularity optimization, but also for more principled ones based on statistical inference and model selection. Here we construct a nested generative model which, through a complete description of the entire network hierarchy at multiple scales, is capable of avoiding this limitation, and enables the detection of modular structure at levels far beyond those possible by current approaches. Even with this increased resolution, the method is based on the principle of parsimony, and is capable of separating signal from noise, and thus will not lead to the identification of spurious modules even on sparse networks. Furthermore, it fully generalizes other approaches in that it is not restricted to purely assortative mixing patterns, directed or undirected graphs, and ad hoc hierarchical structures such as binary trees. Despite its general character, the approach is tractable, and can be combined with advanced techniques of community detection to yield an efficient algorithm which scales well for very large networks.

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Powerlaws and Self-Organized Criticality in Theory and Nature

Powerlaws and Self-Organized Criticality in Theory and Nature | Complex World | Scoop.it

Powerlaws and distributions with heavy tails are common features of many experimentally studied complex systems, like the distribution of the sizes of earthquakes and solar flares, or the duration of neuronal avalanches in the brain. It had been tempting to surmise that a single general concept may act as a unifying underlying generative mechanism, with the theory of self organized criticality being a weighty contender. 
On the theory side there has been, lively activity in developing new and extended models. Three classes of models have emerged. The first line of models is based on a separation between the time scales of drive and dissipation, and includes the original sandpile model and its extensions, like the dissipative earthquake model. Within this approach the steady state is close to criticality in terms of an absorbing phase transition. The second line of approach is based on external drives and internal dynamics competing on similar time scales and includes the coherent noise model, which has a non-critical steady state characterized by heavy-tailed distributions. The third line of modeling proposes a non-critical state which is self-organizing, being guided by an optimization principle, such as the concept of highly optimized tolerance.

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The Year of Climate Departure for World Cities

The Year of Climate Departure for World Cities | Complex World | Scoop.it

The global mean year of climate departure is 2047. The mean for the tropics is 2038, compared to 2053 for all other latitudes. Laboratory of Camilo Mora at University of Hawaii.

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Towards a Proper Assignment of Systemic Risk: The Combined Roles of Network Topology and Shock Characteristics

Towards a Proper Assignment of Systemic Risk: The Combined Roles of Network Topology and Shock Characteristics | Complex World | Scoop.it

The 2007-2008 financial crisis solidified the consensus among policymakers that a macro-prudential approach to regulation and supervision should be adopted. The currently preferred policy option is the regulation of capital requirements, with the main focus on combating procyclicality and on identifying the banks that have a high systemic importance, those that are “too big to fail”. Here we argue that the concept of systemic risk should include the analysis of the system as a whole and we explore systematically the most important properties for policy purposes of networks topology on resistance to shocks. In a thorough study going from analytical models to empirical data, we show two sharp transitions from safe to risky regimes: 1) diversification becomes harmful with just a small fraction (~2%) of the shocks sampled from a fat tailed shock distributions and 2) when large shocks are present a critical link density exists where an effective giant cluster forms and most firms become vulnerable. This threshold depends on the network topology, especially on modularity. Firm size heterogeneity has important but diverse effects that are heavily dependent on shock characteristics. Similarly, degree heterogeneity increases vulnerability only when shocks are directed at the most connected firms. Furthermore, by studying the structure of the core of the transnational corporation network from real data, we show that its stability could be clearly increased by removing some of the links with highest centrality betweeness. Our results provide a novel insight and arguments for policy makers to focus surveillance on the connections between firms, in addition to capital requirements directed at the nodes.

  
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Noise Pollution Maps Crowdsourced from Smartphone Data

Noise Pollution Maps Crowdsourced from Smartphone Data | Complex World | Scoop.it
Noise maps are notoriously time-consuming and expensive to make. Unless you crowdsource the data from smartphones, say Australian engineers.
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Identifying overlapping communities as well as hubs and outliers via nonnegative matrix factorization

Identifying overlapping communities as well as hubs and outliers via nonnegative matrix factorization | Complex World | Scoop.it

Community detection is important for understanding networks. Previous studies observed that communities are not necessarily disjoint and might overlap. It is also agreed that some outlier vertices participate in no community, and some hubs in a community might take more important roles than others. Each of these facts has been independently addressed in previous work. But there is no algorithm, to our knowledge, that can identify these three structures altogether. To overcome this limitation, we propose a novel model where vertices are measured by their centrality in communities, and define the identification of overlapping communities, hubs, and outliers as an optimization problem, calculated by nonnegative matrix factorization.

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Unraveling the origin of exponential law in intra-urban human mobility

Unraveling the origin of exponential law in intra-urban human mobility | Complex World | Scoop.it

The vast majority of travel takes place within cities. Recently, new data has become available which allows for the discovery of urban mobility patterns which differ from established results about long distance travel. Specifically, the latest evidence increasingly points to exponential trip length distributions, contrary to the scaling laws observed on larger scales. In this paper, in order to explore the origin of the exponential law, we propose a new model which can predict individual flows in urban areas better. Based on the model, we explain the exponential law of intra-urban mobility as a result of the exponential decrease in average population density in urban areas. Indeed, both empirical and analytical results indicate that the trip length and the population density share the same exponential decaying rate.

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The Top Five Trend-Setting Cities on Twitter

The Top Five Trend-Setting Cities on Twitter | Complex World | Scoop.it
Twitter data reveals the cities that set trends and those that follow. And the difference may be in the way air passengers carry information across the country, by-passing the Internet, say network scientists.
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Science for a Complex World: Records of conflict and cooperation reveal wisdom of the ages

Science for a Complex World: Records of conflict and cooperation reveal wisdom of the ages | Complex World | Scoop.it

One of the basic principles of science is that good theories extrapolate well. The laws of gravity hold both here and on the Moon, and this universality enables us to land a spacecraft on Mars. Darwin drew the theory of evolution from studies of a remote island in the Pacific, but today we use it to explain the emergence of drug-resistant TB in a city hospital.

The theories of gravity and of evolution are two of our greatest scientific achievements. But in contrast to the universal nature of these laws, our understanding of the human world – the messy realm of newspapers and cafes, traffic jams and gossip, governments and social movements – is remarkably limited.

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