Papers
Follow
Find
184.0K views | +55 today
Papers
Recent publications related to complex systems
Your new post is loading...
Your new post is loading...
Rescooped by Complexity Digest from Non-Equilibrium Social Science
Scoop.it!

Against the Smart City

Against the Smart City | Papers | Scoop.it

Post by Michael Batty

Absolutely the best thing to read on the corporate hype and innuendos from the big computer companies pedalling the idea of ‘the smart city’. Adam Greenfield’s new book – that you can only get on Kindle and which was my first Kindle purchase that I read on my iPad (a success I must say) – is a wonderful and eloquent essay on the extreme hype surrounding the top down new town-like smart cities of Songdo (in South Korea), Masdar (in the UAE), PlanIT Valley (near Paredes in Portugal). He also comments on Singapore, Rio de Janeiro and some of the other established cities who are injecting automation into their urban services and other functions from the top down. His message is that most of the smart cities hype associated with IBM, Cisco, and Siemens amongst others which he recounts in detail is based on the most simplistic of notions as to what a city actually is. 

(...)


Via NESS
more...
Luciano Lampi's curator insight, July 3, 6:30 AM

Smart.....Intelligent.....Complex?

David Week's curator insight, July 14, 3:30 PM

At last someone said it: the "Smart City" is hype.


In fact, whenever you hear the word "smart" associated with regulations ("Smart Code"), policy ("Smart Growth") or technology ("Smart Phones", "Smart Cities") it's hype. Inanimate objects aren't smart. So the most that this can mean is that the regulation, policy or software writers are really smart.


And you have to ask how smart someone can be if they go around touting themselves as smart. Because for me, someone saying they're really smart makes them sound really dumb.

Suggested by Joseph Lizier
Scoop.it!

Current innovations and future challenges of network motif detection

Network motif detection is the search for statistically overrepresented subgraphs present in a larger target network. They are thought to represent key structure and control mechanisms. Although the problem is exponential in nature, several algorithms and tools have been developed for efficiently detecting network motifs. This work analyzes 11 network motif detection tools and algorithms. Detailed comparisons and insightful directions for using these tools and algorithms are discussed. Key aspects of network motif detection are investigated. Network motif types and common network motifs as well as their biological functions are discussed. Applications of network motifs are also presented. Finally, the challenges, future improvements and future research directions for network motif detection are also discussed.

 

Ngoc Tam L. Tran, Sominder Mohan, Zhuoqing Xu, Chun-Hsi Huang
Current innovations and future challenges of network motif detection
Briefings in Bioinformatics (2014), to appear
http://dx.doi.org/10.1093/bib/bbu021

more...
No comment yet.
Scooped by Complexity Digest
Scoop.it!

Multi-scale Integration and Predictability in Resting State Brain Activity

The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales.


Kolchinsky A, Van Den Heuvel M, Griffa A, Hagmann P, Rocha L, Sporns O and Goñi J (2014). Multi-scale Integration and Predictability in Resting State Brain Activity. Front. Neuroinform. 8:66. http://dx.doi.org/10.3389/fninf.2014.00066

more...
No comment yet.
Scooped by Complexity Digest
Scoop.it!

Experimental evidence of massive-scale emotional contagion through social networks

We show, via a massive (N = 689,003) experiment on Facebook, that emotional states can be transferred to others via emotional contagion, leading people to experience the same emotions without their awareness. We provide experimental evidence that emotional contagion occurs without direct interaction between people (exposure to a friend expressing an emotion is sufficient), and in the complete absence of nonverbal cues.


Experimental evidence of massive-scale emotional contagion through social networks
Adam D. I. Kramer, Jamie E. Guillory, and Jeffrey T. Hancock

PNAS  vol. 111 no. 24: 8788–8790, http://dx.doi.org/10.1073/pnas.1320040111

more...
No comment yet.
Scooped by Complexity Digest
Scoop.it!

Studying Collective Human Decision Making and Creativity with Evolutionary Computation

We report a summary of our interdisciplinary research project "Evolutionary Perspective on Collective Decision Making" that was conducted through close collaboration between computational, organizational and social scientists at Binghamton University. We redefined collective human decision making and creativity as evolution of ecologies of ideas, where populations of ideas evolve via continual applications of evolutionary operators such as reproduction, recombination, mutation, selection, and migration of ideas, each conducted by participating humans. Based on this evolutionary perspective, we generated hypotheses about collective human decision making using agent-based computer simulations. The hypotheses were then tested through several experiments with real human subjects. Throughout this project, we utilized evolutionary computation (EC) in non-traditional ways---(1) as a theoretical framework for reinterpreting the dynamics of idea generation and selection, (2) as a computational simulation model of collective human decision making processes, and (3) as a research tool for collecting high-resolution experimental data of actual collaborative design and decision making from human subjects. We believe our work demonstrates untapped potential of EC for interdisciplinary research involving human and social dynamics.


Studying Collective Human Decision Making and Creativity with Evolutionary Computation
Hiroki Sayama, Shelley D. Dionne

http://arxiv.org/abs/1406.6291

more...
No comment yet.
Suggested by Joseph Lizier
Scoop.it!

Transfer Entropy and Transient Limits of Computation

Transfer entropy is a recently introduced information-theoretic measure quantifying directed statistical coherence between spatiotemporal processes, and is widely used in diverse fields ranging from finance to neuroscience. However, its relationships to fundamental limits of computation, such as Landauer's limit, remain unknown. Here we show that in order to increase transfer entropy (predictability) by one bit, heat flow must match or exceed Landauer's limit. Importantly, we generalise Landauer's limit to bi-directional information dynamics for non-equilibrium processes, revealing that the limit applies to prediction, in addition to retrodiction (information erasure). Furthermore, the results are related to negentropy, and to Bremermann's limit and the Bekenstein bound, producing, perhaps surprisingly, lower bounds on the computational deceleration and information loss incurred during an increase in predictability about the process. The identified relationships set new computational limits in terms of fundamental physical quantities, and establish transfer entropy as a central measure connecting information theory, thermodynamics and theory of computation.

 

Transfer Entropy and Transient Limits of Computation
Mikhail Prokopenko and Joseph T. Lizier
Scientific Reports 4, 5394, doi:10.1038/srep05394
http://www.nature.com/srep/2014/140623/srep05394/full/srep05394.html

more...
Colbert Sesanker's curator insight, August 30, 10:40 PM

combine with integrated information

Suggested by eflegara
Scoop.it!

Controllability and observability analysis for vertex domination centrality in directed networks

Topological centrality is a significant measure for characterising the relative importance of a node in a complex network. For directed networks that model dynamic processes, however, it is of more practical importance to quantify a vertex's ability to dominate (control or observe) the state of other vertices. In this paper, based on the determination of controllable and observable subspaces under the global minimum-cost condition, we introduce a novel direction-specific index, domination centrality, to assess the intervention capabilities of vertices in a directed network. Statistical studies demonstrate that the domination centrality is, to a great extent, encoded by the underlying network's degree distribution and that most network positions through which one can intervene in a system are vertices with high domination centrality rather than network hubs. To analyse the interaction and functional dependence between vertices when they are used to dominate a network, we define the domination similarity and detect significant functional modules in glossary and metabolic networks through clustering analysis. The experimental results provide strong evidence that our indices are effective and practical in accurately depicting the structure of directed networks.

 

Controllability and observability analysis for vertex domination centrality in directed networks
B Wang, L Gao, Y Gao, Y Deng, and Y Wang

Scientific Reports 4, Article number 5399 (23 June 2014)

http://dx.doi.org/10.1038/srep05399

more...
No comment yet.
Suggested by eflegara
Scoop.it!

Zipf's law holds for phrases, not words

Over the last century, the elements of many disparate systems have been found to approximately follow Zipf's law---that element size is inversely proportional to element size rank---from city populations, to firm sizes, and family name. But with Zipf's law being originally and most famously observed for word frequency, it is surprisingly limited in its applicability to human language, holding only over a few orders of magnitude before hitting a clear break in scaling. Here, building on the simple observation that a mixture of words and phrases comprise coherent units of meaning in language, we show empirically that Zipf's law for English phrases extends over seven to nine orders of rank magnitude rather than typically two to three for words alone. In doing so, we develop a simple, principled, and scalable method of random phrase partitioning, which crucially opens up a rich frontier of rigorous text analysis via a rank ordering of mixed length phrases rather than words.

 

Zipf's law holds for phrases, not words
JR Williams, PR Lessard, S Desu, E Clark, JP Bagrow, CM Danforth, PS Dodds

http://arxiv.org/abs/1406.5181

more...
No comment yet.
Scooped by Complexity Digest
Scoop.it!

Behaviors and Strategies of Bacterial Navigation in Chemical and Nonchemical Gradients

Bacteria, such as E. coli, live in a complex environment with varying chemical and/or non-chemical stimuli. They constantly seek for and migrate to optimal environmental conditions. A well-known example is E. coli chemotaxis which direct cell movements up or down chemical gradients. Using the same machinery, E. coli can also respond to non-chemical factors (e.g., pH and temperature) and navigate toward certain intermediate, optimal levels of those stimuli. Such taxis behaviors are more sophisticated and require distinctive sensing mechanisms. In this paper, we develop a unified model for different bacterial taxis strategies. This multiscale model incorporates intracellular signaling pathways into population dynamics and leads to a simple theoretical result regarding the steady-state population distribution. Our model can be applied to reveal the key mechanisms for different taxis behaviors and quantitatively account for various experimental data. New predictions can be made within this new model framework to direct future experiments.


Hu B, Tu Y (2014) Behaviors and Strategies of Bacterial Navigation in Chemical and Nonchemical Gradients. PLoS Comput Biol 10(6): e1003672. http://dx.doi.org/10.1371/journal.pcbi.1003672

more...
No comment yet.
Scooped by Complexity Digest
Scoop.it!

Invention as a Combinatorial Process: Evidence from U.S. Patents

Invention has been commonly conceptualized as a search over a space of combinatorial possibilities. Despite the existence of a rich literature, spanning a variety of disciplines, elaborating on the recombinant nature of invention, we lack a formal and quantitative characterization of the combinatorial process underpinning inventive activity. Here we utilize U.S. patent records dating from 1790 to 2010 to formally characterize the invention as a combinatorial process. To do this we treat patented inventions as carriers of technologies and avail ourselves of the elaborate system of technology codes used by the U.S. Patent Office to classify the technologies responsible for an invention's novelty. We find that the combinatorial inventive process exhibits an invariant rate of "exploitation" (refinements of existing combinations of technologies) and "exploration" (the development of new technological combinations). This combinatorial dynamic contrasts sharply with the creation of new technological capabilities -- the building blocks to be combined -- which has significantly slowed down. We also find that notwithstanding the very reduced rate at which new technologies are introduced, the generation of novel technological combinations engenders a practically infinite space of technological configurations.


Invention as a Combinatorial Process: Evidence from U.S. Patents
Hyejin Youn, Luis M. A. Bettencourt, Deborah Strumsky, Jose Lobo

http://arxiv.org/abs/1406.2938

more...
Scooped by Complexity Digest
Scoop.it!

When the bat sings

That bats emit any kind of song comes as a surprise to most people, partly because we tend to think chiefly of their echolocation calls, ultrasonic sounds beyond our hearing, or their short, sharp social calls. It's also a surprise because it is so rare for a mammal to sing like a songbird. “So why do bats?” Bohn asks. “What are the social and environmental pressures that have led them to evolve this ability, which is so mentally demanding?”


When the bat sings
Virginia Morell

Science 20 June 2014:
Vol. 344 no. 6190 pp. 1334-1337
http://dx.doi.org/10.1126/science.344.6190.1334

more...
No comment yet.
Scooped by Complexity Digest
Scoop.it!

Do good actions inspire good actions in others?

Actions such as sharing food and cooperating to reach a common goal have played a fundamental role in the evolution of human societies. These good actions may not maximise the actor's payoff, but they maximise the other's payoff. Consequently, their existence is puzzling for evolutionary theories. Why should you make an effort to help others, even when no reward seems to be at stake? Indeed, experiments typically show that humans are heterogeneous: some may help others, while others may not. With the aim of favouring the emergence of 'successful cultures', a number of studies has recently investigated what mechanisms promote the evolution of a particular good action. But still little is known about if and how good actions can spread from person to person. For instance, does being recipient of an altruistic act increase your probability of being cooperative with others? Plato's quote, 'Good actions give strength to ourselves and inspire good actions in others', suggests that is possible. We have conducted an experiment on Amazon Mechanical Turk to test this mechanism using economic games. We have measured willingness to be cooperative through a standard Prisoner's dilemma and willingness to act altruistically using a binary Dictator game. In the baseline treatments, the endowments needed to play were given by the experimenters, as usual; in the control treatments, they came from a good action made by someone else. Across four different comparisons and a total of 572 subjects, we have never found a significant increase of cooperation or altruism when the endowment came from a good action. We conclude that good actions do not necessarily inspire good actions in others, at least in the ideal scenario of a lab experiment with anonymous subjects.


Do good actions inspire good actions in others?
Valerio Capraro, Alessandra Marcelletti

http://arxiv.org/abs/1406.4294

more...
No comment yet.
Scooped by Complexity Digest
Scoop.it!

Human language reveals a universal positivity bias

Using human evaluation of 100,000 words spread across 24 corpora in 10 languages diverse in origin and culture, we present evidence of a deep imprint of human sociality in language, observing that (1) the words of natural human language possess a universal positivity bias; (2) the estimated emotional content of words is consistent between languages under translation; and (3) this positivity bias is strongly independent of frequency of word usage. Alongside these general regularities, we describe inter-language variations in the emotional spectrum of languages which allow us to rank corpora. We also show how our word evaluations can be used to construct physical-like instruments for both real-time and offline measurement of the emotional content of large-scale texts.


Human language reveals a universal positivity bias
Peter Sheridan Dodds, Eric M. Clark, Suma Desu, Morgan R. Frank, Andrew J. Reagan, Jake Ryland Williams, Lewis Mitchell, Kameron Decker Harris, Isabel M. Kloumann, James P. Bagrow, Karine Megerdoomian, Matthew T. McMahon, Brian F. Tivnan, Christopher M. Danforth

http://arxiv.org/abs/1406.3855

more...
No comment yet.
Suggested by Joseph Lizier
Scoop.it!

Motif statistics of artificially evolved and biological networks

Topological features of gene regulatory networks can be successfully reproduced by a model population evolving under selection for short dynamical attractors. The evolved population of networks exhibit motif statistics, summarized by significance profiles, which closely match those of E. coli, S. cerevsiae, and B. subtilis, in such features as the excess of linear motifs and feedforward loops, and deficiency of feedback loops. The slow relaxation to stasis is a hallmark of a rugged fitness landscape, with independently evolving populations exploring distinct valleys strongly differing in network properties.

 

Burçin Danacı, Mehmet Ali Anıl, and Ayşe Erzan
Motif statistics of artificially evolved and biological networks
Phys. Rev. E 89, 062719 (2014)

more...
No comment yet.
Rescooped by Complexity Digest from Complex World
Scoop.it!

Multiple percolation transitions in a configuration model of a network of networks

Multiple percolation transitions in a configuration model of a network of networks | Papers | Scoop.it

Recently much attention has been paid to the study of the robustness of interdependent and multiplex networks and, in particular, the networks of networks. The robustness of interdependent networks can be evaluated by the size of a mutually connected component when a fraction of nodes have been removed from these networks. Here we characterize the emergence of the mutually connected component in a network of networks in which every node of a network (layer) alpha is connected with q_alpha its randomly chosen replicas in some other networks and is interdependent of these nodes with probability r. We find that when the superdegrees q_alpha of different layers in a network of networks are distributed heterogeneously, multiple percolation phase transition can occur. We show that, depending on the value of r, these transition are continuous or discontinuous.


Via Claudia Mihai
more...
No comment yet.
Scooped by Complexity Digest
Scoop.it!

Complexity Measures and Concept Learning

The nature of concept learning is a core question in cognitive science. Theories must account for the relative difficulty of acquiring different concepts by supervised learners. For a canonical set of six category types, two distinct orderings of classification difficulty have been found. One ordering, which we call paradigm-specific, occurs when adult human learners classify objects with easily distinguishable characteristics such as size, shape, and shading. The general order occurs in all other known cases: when adult humans classify objects with characteristics that are not readily distinguished (e.g., brightness, saturation, hue); for children and monkeys; and when categorization difficulty is extrapolated from errors in identification learning. The paradigm-specific order was found to be predictable mathematically by measuring the logical complexity of tasks, i.e., how concisely the solution can be represented by logical rules. However, logical complexity does not explain the general order. Here we show that a new difficulty measurement, i.e., the amount of uncertainty remaining when a subset of the dimensions are specified, can correctly predict the general order. This result contrasts with the logical-complexity-based task ordering because our proposed measurement captures statistical, not logical, complexity. This suggests that, when learners do not/cannot form logical rules about the characteristics of objects, they may be using statistical means in their category learning. It is known in information science that logical (algorithmic) and statistical (information theoretic) complexities are fundamentally linked. Our proposed statistical complexity measurement, therefore, naturally complements the logical complexity one and extends the overall applicability of the complexity-based approach to understanding concept learning.


Complexity Measures and Concept Learning
Andreas D. Pape, Kenneth J. Kurtz, Hiroki Sayama

http://arxiv.org/abs/1406.7424

more...
No comment yet.
Scooped by Complexity Digest
Scoop.it!

Bell’s theorem still reverberates

Bell’s theorem still reverberates | Papers | Scoop.it

In 1964, Northern Irish physicist John Bell proved mathematically that certain quantum correlations, unlike all other correlations in the Universe, cannot arise from any local cause1. This theorem has become central to both metaphysics and quantum information science. But 50 years on, the experimental verifications of these quantum correlations still have ‘loopholes’, and scientists and philosophers still dispute exactly what the theorem states.


Bell’s theorem still reverberates
Howard Wiseman

Nature 510, 467–469 (26 June 2014) http://dx.doi.org/10.1038/510467a

more...
No comment yet.
Suggested by eflegara
Scoop.it!

Modelling the short term herding behaviour of stock markets

Modelling the behaviour of stock markets has been of major interest in the past century. The market can be treated as a network of many investors reacting in accordance to their group behaviour, as manifested by the index and effected by the flow of external information into the system. Here we devise a model that encapsulates the behaviour of stock markets. The model consists of two terms, demonstrating quantitatively the effect of the individual tendency to follow the group and the effect of the individual reaction to the available information. Using the above factors we were able to explain several key features of the stock market: the high correlations between the individual stocks and the index; the Epps effect; the high fluctuating nature of the market, which is similar to real market behaviour. Furthermore, intricate long term phenomena are also described by this model, such as bursts of synchronized average correlation and the dominance of the index as demonstrated through partial correlation.
 

Modelling the short term herding behaviour of stock markets

Yoash Shapira, Yonatan Berman and Eshel Ben-Jacob

New Journal of Physics 16 053040, 2014.

http://dx.doi.org/10.1088/1367-2630/16/5/053040

more...
No comment yet.
Suggested by eflegara
Scoop.it!

The Strength of the Strongest Ties in Collaborative Problem Solving

Complex problem solving in science, engineering, and business has become a highly collaborative endeavor. Teams of scientists or engineers collaborate on projects using their social networks to gather new ideas and feedback. Here we bridge the literature on team performance and information networks by studying teams' problem solving abilities as a function of both their within-team networks and their members' extended networks. We show that, while an assigned team's performance is strongly correlated with its networks of expressive and instrumental ties, only the strongest ties in both networks have an effect on performance. Both networks of strong ties explain more of the variance than other factors, such as measured or self-evaluated technical competencies, or the personalities of the team members. In fact, the inclusion of the network of strong ties renders these factors non-significant in the statistical analysis. Our results have consequences for the organization of teams of scientists, engineers, and other knowledge workers tackling today's most complex problems.

 

The Strength of the Strongest Ties in Collaborative Problem Solving
Yves-Alexandre de Montjoye, Arkadiusz Stopczynski, Erez Shmueli, Alex Pentland, and Sune Lehmann

Scientific Reports 4, Article number: 5277 (2014)

http://dx.doi.org/10.1038/srep05277

more...
tom cockburn's curator insight, June 25, 2:06 PM

Interesting results

Scooped by Complexity Digest
Scoop.it!

Good Art Is Popular Because It's Good. Right?

Good Art Is Popular Because It's Good. Right? | Papers | Scoop.it
Research suggests that after a basic standard of quality is met, what becomes a success and what doesn't is essentially a matter of chance.


http://www.npr.org/2014/02/27/282939233/good-art-is-popular-because-its-good-right

more...
Minsik Oh's curator insight, June 26, 4:55 AM

Inherent quality of art

Scooped by Complexity Digest
Scoop.it!

A minimal model captures the collective behaviour of locusts

Locusts and other migrating insects form cohesive swarms that travel over huge distances and can have a devastating effect on crops, leading to famine and starvation. Understanding the factors that enable the long-term cohesion of such swarms is therefore of paramount importance. When placed in an annular arena, a population of locusts march together in a common direction, which may be reversed at later times. These directional switches are more frequent at lower population numbers. We propose a novel, minimal, spatially-homogenous model of locust interactions to investigate the individual-based mechanisms of the observed density-dependent macroscopic-level effect. This model successfully replicates the density-dependent properties of the experimental data as a consequence of the demographic noise inherent at low population numbers. The ability of our non-spatial model to replicate the experimental data indicates that the switching behaviour is a fundamental property of the way locusts interact rather than an effect of the environmental geometry. However, to match the data it is necessary to include higher-order interactions in the model, indicating that locusts can incorporate information from at least two neighbouring individuals travelling in the opposite direction. We derive a stochastic differential equation from our individual-based model, and demonstrate agreement between its drift and diffusion coefficients and those calculated numerically directly from the experimental data. Using the experimental data to parameterise our model, we demonstrate that the model replicates both the qualitative form of the time-dependent data and quantitative statistics such as the mean switching time and stationary probability distribution.


A minimal model captures the collective behaviour of locusts
Christian A. Yates, Louise Dyson, Jerome Buhl, Alan J. McKane

http://arxiv.org/abs/1406.5585

more...
No comment yet.
Rescooped by Complexity Digest from Complex World
Scoop.it!

Spatial correlation analysis of cascading failures: Congestions and Blackouts

Spatial correlation analysis of cascading failures: Congestions and Blackouts | Papers | Scoop.it
Cascading failures have become major threats to network robustness due to their potential catastrophic consequences, where local perturbations can induce global propagation of failures. Unlike failures spreading via direct contacts due to structural interdependencies, overload failures usually propagate through collective interactions among system components. Despite the critical need in developing protection or mitigation strategies in networks such as power grids and transportation, the propagation behavior of cascading failures is essentially unknown. Here we find by analyzing our collected data that jams in city traffic and faults in power grid are spatially long-range correlated with correlations decaying slowly with distance. Moreover, we find in the daily traffic, that the correlation length increases dramatically and reaches maximum, when morning or evening rush hour is approaching. Our study can impact all efforts towards improving actively system resilience ranging from evaluation of design schemes, development of protection strategies to implementation of mitigation programs.

Via Claudia Mihai
more...
tom cockburn's curator insight, June 25, 2:08 PM

Could be far reaching in its significance

Scooped by Complexity Digest
Scoop.it!

The cultural evolution of mind reading

It is not just a manner of speaking: “Mind reading,” or working out what others are thinking and feeling, is markedly similar to print reading. Both of these distinctly human skills recover meaning from signs, depend on dedicated cortical areas, are subject to genetically heritable disorders, show cultural variation around a universal core, and regulate how people behave. But when it comes to development, the evidence is conflicting. Some studies show that, like learning to read print, learning to read minds is a long, hard process that depends on tuition. Others indicate that even very young, nonliterate infants are already capable of mind reading. Here, we propose a resolution to this conflict. We suggest that infants are equipped with neurocognitive mechanisms that yield accurate expectations about behavior (“automatic” or “implicit” mind reading), whereas “explicit” mind reading, like literacy, is a culturally inherited skill; it is passed from one generation to the next by verbal instruction.


The cultural evolution of mind reading

Cecilia M. Heyes, Chris D. Frith

Science 20 June 2014:
Vol. 344 no. 6190
http://dx.doi.org/10.1126/science.1243091

more...
No comment yet.
Scooped by Complexity Digest
Scoop.it!

Gossip: Identifying Central Individuals in a Social Network

We examine individuals' abilities to identify the highly central people in their social networks, where centrality is defined by diffusion centrality (Banerjee et al., 2013), which characterizes a node's influence in spreading information. We first show that diffusion centrality nests standard centrality measures -- degree, eigenvector and Katz-Bonacich centrality -- as extreme special cases. Next, we show that boundedly rational individuals can, simply by tracking sources of gossip, identify who is central in their social network in the specific sense of having high diffusion centrality. Finally, we examine whether the model's predictions are consistent with data in which we ask people in each of 35 villages whom would be the most effective point from which to initiate a diffusion process. We find that individuals accurately nominate central individuals in the diffusion centrality sense. Additionally, the nominated individuals are more central in the network than "village leaders" as well as those who are most central in a GPS sense. This suggests that individuals can rank others according to their centrality in the networks even without knowing the network, and that eliciting network centrality of others simply by asking individuals may be an inexpensive research and policy tool.


Gossip: Identifying Central Individuals in a Social Network
Abhijit Banerjee, Arun G. Chandrasekhar, Esther Duflo, Matthew O. Jackson

more...
No comment yet.
Scooped by Complexity Digest
Scoop.it!

The Billion Cell Construct: Will Three-Dimensional Printing Get Us There?

The Billion Cell Construct: Will Three-Dimensional Printing Get Us There? | Papers | Scoop.it

How structure relates to function—across spatial scales, from the single molecule to the whole organism—is a central theme in biology. Bioengineers, however, wrestle with the converse question: will function follow form? That is, we struggle to approximate the architecture of living tissues experimentally, hoping that the structure we create will lead to the function we desire. A new means to explore the relationship between form and function in living tissue has arrived with three-dimensional printing, but the technology is not without limitations.


Miller JS (2014) The Billion Cell Construct: Will Three-Dimensional Printing Get Us There? PLoS Biol 12(6): e1001882. http://dx.doi.org/10.1371/journal.pbio.1001882

more...
No comment yet.