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Making big data work: smart, sustainable, and safe cities

The goal of the present thematic series is to showcase some of the most relevant contributions submitted to the ‘Telecom Italia Big Data Challenge 2014’ and to provide a discussion venue about recent advances in the appplication of mobile phone and social media data to the study of individual and collective behaviors. Particular attention is devoted to data-driven studies aimed at understanding city dynamics. These studies include: modeling individual and collective traffic patterns and automatically identifying areas with traffic congestion, creating high-resolution population estimates for Milan inhabitants, clustering urban dynamics of migrants and visitors traveling to a city for business or tourism, and investigating the relationship between urban communication and urban happiness.


Making big data work: smart, sustainable, and safe cities
Bruno Lepri, Fabrizio Antonelli, Fabio Pianesi and Alex Pentland

EPJ Data Science 2015, 4:16  http://dx.doi.org/10.1140/epjds/s13688-015-0050-4 ;

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ComplexInsight's curator insight, October 26, 2015 12:48 PM

Interesting results of Telecom Italia's 2014 Bid Data Challenge - if smart cities are of interest  - worth reading.

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Quantifying randomness in real networks

Quantifying randomness in real networks | Papers | Scoop.it

Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks—the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain—and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs.


Quantifying randomness in real networks
• Chiara Orsini, Marija M. Dankulov, Pol Colomer-de-Simón, Almerima Jamakovic, Priya Mahadevan, Amin Vahdat, Kevin E. Bassler, Zoltán Toroczkai, Marián Boguñá, Guido Caldarelli, Santo Fortunato & Dmitri Krioukov

Nature Communications 6, Article number: 8627 http://dx.doi.org/10.1038/ncomms9627

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The rise of fully turbulent flow

Over a century of research into the origin of turbulence in wall-bounded shear flows has resulted in a puzzling picture in which turbulence appears in a variety of different states competing with laminar background flow. At moderate flow speeds, turbulence is confined to localized patches; it is only at higher speeds that the entire flow becomes turbulent. The origin of the different states encountered during this transition, the front dynamics of the turbulent regions and the transformation to full turbulence have yet to be explained. By combining experiments, theory and computer simulations, here we uncover a bifurcation scenario that explains the transformation to fully turbulent pipe flow and describe the front dynamics of the different states encountered in the process. Key to resolving this problem is the interpretation of the flow as a bistable system with nonlinear propagation (advection) of turbulent fronts. These findings bridge the gap between our understanding of the onset of turbulence and fully turbulent flows.


The rise of fully turbulent flow
• Dwight Barkley, Baofang Song, Vasudevan Mukund, Grégoire Lemoult, Marc Avila & Björn Hof

Nature 526, 550–553 (22 October 2015) http://dx.doi.org/10.1038/nature15701

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Marcelo Errera's curator insight, October 26, 2015 4:51 PM

When seen like this, organization replaces complexity.  

Very interesting paper.

 

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Neuroscience: Connectomes make the map

Neuroscience: Connectomes make the map | Papers | Scoop.it

The subjects studied by connectome researchers range from living people to the preserved brains of tiny animals such as worms and flies. The investigative technologies range from MRI scanners to light microscopes and electron microscopes. Irrespective of the specifics, scientists — with the aid of computers — painstakingly chart connections to build an atlas. The map-makers hope that revealing the connectome's structure will help neuroscientists to navigate as they work out how different parts of the brain function together.


Neuroscience: Connectomes make the map
Amber Dance
Nature 526, 147–149 (01 October 2015) http://dx.doi.org/10.1038/526147a

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Inequality and visibility of wealth in experimental social network

Humans prefer relatively equal distributions of resources1, 2, 3, 4, 5, yet societies have varying degrees of economic inequality6. To investigate some of the possible determinants and consequences of inequality, here we perform experiments involving a networked public goods game in which subjects interact and gain or lose wealth. Subjects (n = 1,462) were randomly assigned to have higher or lower initial endowments, and were embedded within social networks with three levels of economic inequality (Gini coefficient = 0.0, 0.2, and 0.4). In addition, we manipulated the visibility of the wealth of network neighbours. We show that wealth visibility facilitates the downstream consequences of initial inequality—in initially more unequal situations, wealth visibility leads to greater inequality than when wealth is invisible. This result reflects a heterogeneous response to visibility in richer versus poorer subjects. We also find that making wealth visible has adverse welfare consequences, yielding lower levels of overall cooperation, inter-connectedness, and wealth. High initial levels of economic inequality alone, however, have relatively few deleterious welfare effects.


Inequality and visibility of wealth in experimental social networks
• Akihiro Nishi, Hirokazu Shirado, David G. Rand & Nicholas A. Christakis

Nature 526, 426–429 (15 October 2015) http://dx.doi.org/10.1038/nature15392

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Toward a unifying framework for evolutionary processes

The theory of population genetics and evolutionary computation have been evolving separately for nearly 30 years. Many results have been independently obtained in both fields and many others are unique to its respective field. We aim to bridge this gap by developing a unifying framework for evolutionary processes that allows both evolutionary algorithms and population genetics models to be cast in the same formal framework.


Toward a unifying framework for evolutionary processes
Tiago Paixão, et al.

Journal of Theoretical Biology
Volume 383, 21 October 2015, Pages 28–43

http://dx.doi.org/10.1016/j.jtbi.2015.07.011

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ComplexInsight's curator insight, October 22, 2015 4:59 AM

Interesting paper - however any paper discussing an approach to a unifying evolutionary process that discusses genetic algorithms is somewhat of a remis when doing a recap and missing John H Holland's pioneering work.   That said still worth reading.

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Cross-boundary Behavioural Reprogrammability of Cellular Automata from Emulation Networks

We explore the reprogramming capabilities of computer programs using cellular automata (CA). We show a series of boundary crossing results, including a Wolfram Class 1 Elementary Cellular Automaton (ECA) emulating a Class 2 ECA, a Class 2 ECA emulating a Class 3 ECA, and a Class 3 ECA emulating a Class 2 ECA, along with results of a similar type for general CA (neighbourhood range r=3/2), including a Class 1 CA emulating a Class 3 CA, Classes 3 and 4 CAs emulating Class 4 CAs, and Class 4 emulating Class 3 CAs. All these emulations occur with only a constant overhead, and hence are computationally efficient. By constructing emulation networks through an exhaustive search in the compiler space, we show that topological properties determining emulation direction, such as ingoing and outgoing hub degrees, suggest a topological classification of class 4 behaviour consistent with Turing universality conjectures. We also found that no hacking strategy based on compiler complexity or compiler similarity is suggested. We also introduce a definition of prime rules applicable to CAs-- analogous to that of prime numbers--according to which CA rules act as basic constructors of all other rules. We show a Turing universality result of a composition of ECA rules emulating rule 110. The approach yields a novel perspective on complexity, controllability, causality, and reprogrammability of even the simplest computer programs providing strong evidence that computation universality is ubiquitous. The results suggest that complexity is, or can be, generally driven by initial conditions, and are therefore in this sense more fundamental than even the underlying rules that we show can asymptotically carry any desired computation.


Cross-boundary Behavioural Reprogrammability of Cellular Automata from Emulation Networks
Jürgen Riedel, Hector Zenil

http://arxiv.org/abs/1510.01671

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ComplexInsight's curator insight, October 22, 2015 5:07 AM

Cellular automata are such a simple delightful and deeply compelling - good discussion of their value in looking into inherent complexity of systems

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PAFit: A Statistical Method for Measuring Preferential Attachment in Temporal Complex Networks

Preferential attachment is a stochastic process that has been proposed to explain certain topological features characteristic of complex networks from diverse domains. The systematic investigation of preferential attachment is an important area of research in network science, not only for the theoretical matter of verifying whether this hypothesized process is operative in real-world networks, but also for the practical insights that follow from knowledge of its functional form. Here we describe a maximum likelihood based estimation method for the measurement of preferential attachment in temporal complex networks. We call the method PAFit, and implement it in an R package of the same name. PAFit constitutes an advance over previous methods primarily because we based it on a nonparametric statistical framework that enables attachment kernel estimation free of any assumptions about its functional form. We show this results in PAFit outperforming the popular methods of Jeong and Newman in Monte Carlo simulations. What is more, we found that the application of PAFit to a publically available Flickr social network dataset yielded clear evidence for a deviation of the attachment kernel from the popularly assumed log-linear form. Independent of our main work, we provide a correction to a consequential error in Newman’s original method which had evidently gone unnoticed since its publication over a decade ago.


Pham T, Sheridan P, Shimodaira H (2015) PAFit: A Statistical Method for Measuring Preferential Attachment in Temporal Complex Networks. PLoS ONE 10(9): e0137796. http://dx.doi.org/10.1371/journal.pone.0137796

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A century of physics

A century of physics | Papers | Scoop.it

An analysis of Web of Science data spanning more than 100 years reveals the rapid growth and increasing multidisciplinarity of physics — as well its internal map of subdisciplines.


A century of physics
Roberta Sinatra, Pierre Deville, Michael Szell, Dashun Wang & Albert-László Barabási

Nature Physics 11, 791–796 (2015) http://dx.doi.org/10.1038/nphys3494 

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Personalization in practice

Last month, an advisory committee released recommendations for recruiting at least 1 million individuals to participate in the U.S. National Institutes of Health's Precision Medicine Initiative. This bold approach to disease treatment and prevention seeks to account for an individual's genes, environment, and lifestyle to improve health outcomes. The ability to collect, integrate, analyze, and model relevant data streams is central to this effort. Moving beyond “just” massive data collection will require structured convergence among various disciplines. So, how should data be gathered? Here, computational modeling can be a useful guide. Modeling at the molecular, cellular, tissue, and organismal level will be essential to identify the molecular interactions that underlie progressive diseases and to generate a comprehensive and dynamic picture of the individual.


Personalization in practice
Ravi Iyengar, Russ B. Altman, Olga Troyanskya, Garret A. FitzGerald

Science 16 October 2015:
Vol. 350 no. 6258 pp. 282-283
http://dx.doi.org/10.1126/science.aad5204 ;

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Calculating entropy at different scales among diverse communication systems

We evaluated the impact of changing the observation scale over the entropy measures for text descriptions. MIDI coded Music, computer code and two human natural languages were studied at the scale of characters, words, and at the Fundamental Scale resulting from adjusting the symbols length used to interpret each text-description until it produced minimum entropy. The results show that the Fundamental Scale method is comparable with the use of words when measuring entropy levels in written texts. However, this method can also be used in communication systems lacking words such as music. Measuring symbolic entropy at the fundamental scale allows to calculate quantitatively, relative levels of complexity for different communication systems. The results open novel vision on differences among the structure of the communication systems studied.


Calculating entropy at different scales among diverse communication systems
Gerardo Febres, Klaus Jaffe

http://arxiv.org/abs/1510.01026

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Urban Scaling in Europe

Over the last decades, in disciplines as diverse as economics, geography, and complex systems, a perspective has arisen proposing that many properties of cities are quantitatively predictable due to agglomeration or scaling effects. Using new harmonized definitions for functional urban areas, we examine to what extent these ideas apply to European cities. We show that while most large urban systems in Western Europe (France, Germany, Italy, Spain, UK) approximately agree with theoretical expectations, the small number of cities in each nation and their natural variability preclude drawing strong conclusions. We demonstrate how this problem can be overcome so that cities from different urban systems can be pooled together to construct larger datasets. This leads to a simple statistical procedure to identify urban scaling relations, which then clearly emerge as a property of European cities. We compare the predictions of urban scaling to Zipf's law for the size distribution of cities and show that while the former holds well the latter is a poor descriptor of European cities. We conclude with scenarios for the size and properties of future pan-European megacities and their implications for the economic productivity, technological sophistication and regional inequalities of an integrated European urban system.


Urban Scaling in Europe
Luis M. A. Bettencourt, Jose Lobo

http://arxiv.org/abs/1510.00902

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Exploration and Exploitation of Victorian Science in Darwin's Reading Notebooks

Search in an environment with an uncertain distribution of resources involves a trade-off between local exploitation and distant exploration. This extends to the problem of information foraging, where a knowledge-seeker shifts between reading in depth and studying new domains. To study this, we examine the reading choices made by one of the most celebrated scientists of the modern era: Charles Darwin. Darwin built his theory of natural selection in part by synthesizing disparate parts of Victorian science. When we analyze his extensively self-documented reading we find shifts, on multiple timescales, between choosing to remain with familiar topics and seeking cognitive surprise in novel fields. On the longest timescales, these shifts correlate with major intellectual epochs of his career, as detected by Bayesian epoch estimation. When we compare Darwin's reading path with publication order of the same texts, we find Darwin more adventurous than the culture as a whole.


Exploration and Exploitation of Victorian Science in Darwin's Reading Notebooks
Jaimie Murdock, Colin Allen, Simon DeDeo

http://arxiv.org/abs/1509.07175

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Biodiversity increases the resistance of ecosystem productivity to climate extremes

Data from experiments that manipulated grassland biodiversity across Europe and North America show that biodiversity increases an ecosystem’s resistance to, although not resilience after, climate extremes.


Biodiversity increases the resistance of ecosystem productivity to climate extremes
◦ Forest Isbell, Dylan Craven, John Connolly, Michel Loreau, Bernhard Schmid+ et al.

Nature 526, 574–577 (22 October 2015) http://dx.doi.org/10.1038/nature15374

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A global reference for human genetic variation

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.


A global reference for human genetic variation
• The 1000 Genomes Project Consortium

Nature 526, 68–74 (01 October 2015) http://dx.doi.org/10.1038/nature15393

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The tantalizing links between gut microbes and the brain

The tantalizing links between gut microbes and the brain | Papers | Scoop.it
Neuroscientists are probing the idea that intestinal microbiota might influence brain development and behaviour.


http://www.nature.com/news/the-tantalizing-links-between-gut-microbes-and-the-brain-1.18557 

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Out of the darkness

For years, physicians assumed that once a blind person passed a critical age in early childhood without regaining vision, their brain would never be able to make sense of the visual world. A project called Prakash has demolished that assumption. Since 2004, project eye surgeons have removed congenital cataracts from hundreds of blind children, teenagers and young adults in India, restoring their sight. The surprising capacity of Prakash patients to regain substantial vision is rewriting our understanding of visual neuroscience. While probing how the newly sighted process visual cues, project scientists are peeling away layers of mystery about which aspects of sight come preprogrammed and which are shaped by experience.


Out of the darkness
Rhitu Chatterjee

Science 23 October 2015:
Vol. 350 no. 6259 pp. 372-375
http://dx.doi.org/10.1126/science.350.6259.372 ;

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The complexity of wicked problems in large scale change

The paper provides implications for LSC and action steps for change agents in organizations, arguing that by understanding change initiatives through the lenses of complexity and wicked problems, change agents are likely to be more effective.


Sandra Waddock , Greta M. Meszoely , Steve Waddell , Domenico Dentoni, (2015) "The complexity of wicked problems in large scale change", Journal of Organizational Change Management, Vol. 28 Iss: 6, pp.993 - 1012
http://dx.doi.org/10.1108/JOCM-08-2014-0146

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Classification and unification of the microscopic deterministic traffic models

We identify a universal mathematical structure in microscopic deterministic traffic models (with identical drivers), and thus we show that all such existing models in the literature, including both the two-phase and three-phase models, can be understood as special cases of a master model by expansion around a set of well-defined ground states. This allows any two traffic models to be properly compared and identified. The three-phase models are characterized by the vanishing of leading orders of expansion within a certain density range, and as an example the popular intelligent driver model is shown to be equivalent to a generalized optimal velocity (OV) model. We also explore the diverse solutions of the generalized OV model that can be important both for understanding human driving behaviors and algorithms for autonomous driverless vehicles.

 

Classification and unification of the microscopic deterministic traffic models

Bo Yang and Christopher Monterola
Phys. Rev. E 92, 042802 – Published 2 October 2015

DOI http://dx.doi.org/10.1103/PhysRevE.92.042802

 

 

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Enhancing disease surveillance with novel data streams: challenges and opportunities

Novel data streams (NDS), such as web search data or social media updates, hold promise for enhancing the capabilities of public health surveillance. In this paper, we outline a conceptual framework for integrating NDS into current public health surveillance. Our approach focuses on two key questions: What are the opportunities for using NDS and what are the minimal tests of validity and utility that must be applied when using NDS? Identifying these opportunities will necessitate the involvement of public health authorities and an appreciation of the diversity of objectives and scales across agencies at different levels (local, state, national, international). We present the case that clearly articulating surveillance objectives and systematically evaluating NDS and comparing the performance of NDS to existing surveillance data and alternative NDS data is critical and has not sufficiently been addressed in many applications of NDS currently in the literature.


Enhancing disease surveillance with novel data streams: challenges and opportunities
Benjamin M Althouse, Samuel V Scarpino, et al.

EPJ Data Science 2015, 4:17  http://dx.doi.org/10.1140/epjds/s13688-015-0054-0 ;

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What You Gotta Know to Play Good in the Iterated Prisoner’s Dilemma

Here we describe all the memory-one good strategies for the non-symmetric version of the Prisoner’s Dilemma.  We discuss the special advantages and problems associated with some specific good strategies.


What You Gotta Know to Play Good in the Iterated Prisoner’s Dilemma
Ethan Akin

Games 2015, 6(3), 175-190; http://dx.doi.org/10.3390/g6030175

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Quantifying socio-economic indicators in developing countries from mobile phone communication data: applications to Côte d’Ivoire

The widespread adoption of mobile devices that record the communications, social relations, and movements of billions of individuals in great detail presents unique opportunities for the study of social structures and human dynamics at very large scales. This is particularly the case for developing countries where social and economic data can be hard to obtain and is often too sparse for real-time analytics. Here we leverage mobile call log data from Côte d’Ivoire to analyze the relations between its nation-wide communications network and the socio-economic dynamics of its regional economies. We introduce the CallRank indicator to quantify the relative importance of an area on the basis of call records, and show that a region’s ratio of in- and out-going calls can predict its income level. We detect a communication divide between rich and poor regions of Côte d’Ivoire, which corresponds to existing socio-economic data. Our results demonstrate the potential of mobile communication data to monitor the economic development and social dynamics of low-income developing countries in the absence of extensive econometric and social data. Our work may support efforts to stimulate sustainable economic development and to reduce poverty and inequality.


Quantifying socio-economic indicators in developing countries from mobile phone communication data: applications to Côte d’Ivoire
Huina Mao, Xin Shuai, Yong-Yeol Ahn and Johan Bollen

EPJ Data Science 2015, 4:15  http://dx.doi.org/10.1140/epjds/s13688-015-0053-1 ;

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The Immigration ‘Boogeyman’: Separating Fact from Fiction

The Immigration ‘Boogeyman’: Separating Fact from Fiction | Papers | Scoop.it

The immigrants are coming, and several Republicans vying for the presidential nomination are arguing that the U.S. may be in jeopardy. We should repel immigrants by building walls along the Canadian or Mexican borders, some suggest. If elected, New Jersey governor Chris Christie promises to track immigrants the same way FedEx tracks packages. We must expel those already here through mass deportations, says Donald Trump. “They’re bringing drugs. They’re bringing crime. They’re rapists. And some, I assume, are good people,” Trump said recently about Mexican immigrants.
Who the “good people” are and are not may be a matter of opinion, but actual data might help ease any worries about the economy and waves of crime. “In reality, immigrants do not commit a lot of crime,” says Emily Owens, a University of Pennsylvania professor of criminology and Wharton professor of business economics and public policy. “The immigrant crime rate is very low compared to native people. This idea that immigrants commit a lot of crime — there is no evidence.”


http://knowledge.wharton.upenn.edu/article/the-immigration-boogeyman-separating-fact-from-fiction/?utm_source=kw_newsletter&utm_medium=email&utm_campaign=2015-09-30 

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Networkcontrology

An increasing number of complex systems are now modeled as networks of coupled dynamical entities. Nonlinearity and high-dimensionality are hallmarks of the dynamics of such networks but have generally been regarded as obstacles to control. Here, I discuss recent advances on mathematical and computational approaches to control high-dimensional nonlinear network dynamics under general constraints on the admissible interventions. I also discuss the potential of network control to address pressing scientific problems in various disciplines.


Networkcontrology, 
Adilson E. Motter, 
Chaos 25, 097621 (2015)
http://dx.doi.org/10.1063/1.4931570 

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Detecting global bridges in networks

The identification of nodes occupying important positions in a network structure is crucial for the understanding of the associated real-world system. Usually, betweenness centrality is used to evaluate a node capacity to connect different graph regions. However, we argue here that this measure is not adapted for that task, as it gives equal weight to "local" centers (i.e. nodes of high degree central to a single region) and to "global" bridges, which connect different communities. This distinction is important as the roles of such nodes are different in terms of the local and global organisation of the network structure. In this paper we propose a decomposition of betweenness centrality into two terms, one highlighting the local contributions and the other the global ones. We call the latter bridgeness centrality and show that it is capable to specifically spot out global bridges. In addition, we introduce an effective algorithmic implementation of this measure and demonstrate its capability to identify global bridges in air transportation and scientific collaboration networks.


Detecting global bridges in networks
Pablo Jensen, Matteo Morini, Marton Karsai, Tommaso Venturini, Alessandro Vespignani, Mathieu Jacomy, Jean-Philippe Cointet, Pierre Merckle, Eric Fleury

http://arxiv.org/abs/1509.08295

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Barry Schachter's curator insight, October 10, 2015 4:25 PM

financial networks, too!

Liz Rykert's curator insight, October 11, 2015 10:55 AM

This paper looks useful from the perspective of finding and supporting key nodes who help the whole network connect.