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Romantic Partnerships and the Dispersion of Social Ties: A Network Analysis of Relationship Status on Facebook

A crucial task in the analysis of on-line social-networking systems is to identify important people --- those linked by strong social ties --- within an individual's network neighborhood. Here we investigate this question for a particular category of strong ties, those involving spouses or romantic partners. We organize our analysis around a basic question: given all the connections among a person's friends, can you recognize his or her romantic partner from the network structure alone? Using data from a large sample of Facebook users, we find that this task can be accomplished with high accuracy, but doing so requires the development of a new measure of tie strength that we term `dispersion' --- the extent to which two people's mutual friends are not themselves well-connected. The results offer methods for identifying types of structurally significant people in on-line applications, and suggest a potential expansion of existing theories of tie strength.

 

Romantic Partnerships and the Dispersion of Social Ties: A Network Analysis of Relationship Status on Facebook
Lars Backstrom, Jon Kleinberg

http://arxiv.org/abs/1310.6753


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Libros y Papers sobre  Complejidad - Sistemas Complejos
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How Network Science Is Changing Our Understanding of Law | MIT Technology Review

How Network Science Is Changing Our Understanding of Law | MIT Technology Review | Libros y Papers sobre  Complejidad - Sistemas Complejos | Scoop.it
The first network analysis of the entire body of European Community legislation reveals the pattern of links between laws and their resilience to change.
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Reconstructing Reality: Models, Mathematics, and Simulations (Oxford Studies in Philosophy of Science): Margaret Morrison: 9780199380275: Amazon.com: Books

Reconstructing Reality: Models, Mathematics, and Simulations (Oxford Studies in Philosophy of Science)

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Reconstructing Reality: Models, Mathematics, and Simulations (Oxford Studies in Philosophy of Science) [Margaret Morrison] on Amazon.com. *FREE* shipping on qualifying offers. Attempts to understand various aspects of the empirical world often rely on modelling processes that involve a reconstruction of systems under investigation. Typically the reconstruction uses mathematical frameworks like gauge theory and renormalization group methods
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Cognition and behavior

An important question in the debate over embodied, enactive, and extended cognition has been what has been meant by “cognition”. What is this cognition that is supposed to be embodied, enactive, or extended? Rather than undertake a frontal assault on this question, however, this paper will take a different approach. In particular, we may ask how cognition is supposed to be related to behavior. First, we could ask whether cognition is supposed to be (a type of) behavior. Second, we could ask whether we should attempt to understand cognitive processes in terms of antecedently understood cognitive behaviors. This paper will survey some of the answers that have been (implicitly or explicitly) given in the embodied, enactive, and extended cognition literature, then suggest reasons to believe that we should answer both questions in the negative.

 

Cognition and behavior
Ken Aizawa

Synthese
January 2015

http://dx.doi.org/10.1007/s11229-014-0645-5 ;


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A Unifying Theory for Scaling Laws of Human Populations

The spatial distribution of people exhibits clustering across a wide range of scales, from household to continental  scales. Empirical data indicates simple power-law scalings for the size distribution of cities (known as Zipf's law), the geographic distribution of friends, and the population density fluctuations as a function of scale. We derive a simple statistical model that explains all of these scaling laws based on a single unifying principle involving the random spatial growth of clusters of people on all scales. The model makes important new predictions for the spread of diseases and other social phenomena.

 

A Unifying Theory for Scaling Laws of Human Populations
Henry W. Lin, Abraham Loeb

http://arxiv.org/abs/1501.00738


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Infrastructure Complexity | Full text | Development, information and social connectivity in Côte d¿Ivoire

Understanding human socioeconomic development has proven to be one of the most difficult and persistent problems in science and policy. Traditional policy has often attempted to promote human development through infrastructure and the delivery of services, but the link between these engineered systems and the complexity of human socioeconomic behavior remains poorly understood. Recent research suggests that the key to socioeconomic progress lies in the development of processes whereby new information is created by individuals and organizations and embedded in the structure of social networks at a diverse set of scales, from nations to cities to firms. Here, we formalize these ideas in terms of network theory—namely the spatial network of mobile phone communications in Côte d’Ivoire--to show how incipient socioeconomic connectivity may constitute a general obstacle to development. Inspired by recent progress in the theory of cities as complex systems, we then propose a set of tests for these theories using telecommunications network data and describe how telecommunication services may generally help promote socioeconomic development.
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Follow the Leader: Herding Behavior in Heterogeneous Populations

Here we study the emergence of spontaneous leadership in large populations. In standard models of opinion dynamics, herding behavior is only obeyed at the local scale due to the interaction of single agents with their neighbors; while at the global scale, such models are governed by purely diffusive processes. Surprisingly, in this paper we show that the combination of a strong separation of time scales within the population and a hierarchical organization of the influences of some agents on the others induces a phase transition between a purely diffusive phase, as in the standard case, and a herding phase where a fraction of the agents self-organize and lead the global opinion of the whole population.

 

Follow the Leader: Herding Behavior in Heterogeneous Populations
Guillem Mosquera-Donate, Marian Boguna

http://arxiv.org/abs/1412.7427


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Generalized Lyapunov exponent as a unified characterization of dynamical instabilities

The Lyapunov exponent characterizes an exponential growth rate of the difference of nearby orbits. A positive Lyapunov exponent is a manifestation of chaos. Here, we propose the Lyapunov pair, which is based on the generalized Lyapunov exponent, as a unified characterization of non-exponential and exponential dynamical instabilities in one-dimensional maps. Chaos is classified into three different types, i.e., super-exponential, exponential, and sub-exponential dynamical instabilities. Using one-dimensional maps, we demonstrate super-exponential and sub-exponential chaos and quantify the dynamical instabilities by the Lyapunov pair. In sub-exponential chaos, we show super-weak chaos, which means that the growth of the difference of nearby orbits is slower than a stretched exponential growth. The scaling of the growth is analytically studied by a recently developed theory of a continuous accumulation process, which is related to infinite ergodic theory.


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Complexity and the Economy: W. Brian Arthur

Complexity and the Economy

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Complexity and the Economy [W. Brian Arthur] on Amazon.com. *FREE* shipping on qualifying offers. 

 

Economics is changing. In the last few years it has generated a number of new approaches. One of the most promising -complexity economics - was pioneered in the 1980s and 1990s by a small team at the Santa Fe Institute. Economist and complexity theorist W. Brian Arthur led that team, and in this book he collects many of his articles on this new approach. The traditional framework sees behavior in the economy as in an equilibrium steady state. People in the economy face well-defined problems and use perfect deductive reasoning to base their actions on. The complexity framework, by contrast, sees the economy as always in process, always changing. People try to make sense of the situations they face using whatever reasoning they have at hand, and together create outcomes they must individually react to anew. The resulting economy is not a well-ordered machine, but a complex evolving system that is imperfect, perpetually constructing itself anew, and brimming with vitality. 

The new vision complements and widens the standard one, and it helps answer many questions: Why does the stock market show moods and a psychology? Why do high-tech markets tend to lock in to the dominance of one or two very large players? How do economies form, and how do they continually alter in structure over time? 

The papers collected here were among the first to use evolutionary computation, agent-based modeling, and cognitive psychology. They cover topics as disparate as how markets form out of beliefs; how technology evolves over the long span of time; why systems and bureaucracies get more complicated as they evolve; and how financial crises can be foreseen and prevented in the future.

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Global Civil Unrest: Contagion, Self-Organization, and Prediction

Global Civil Unrest: Contagion, Self-Organization, and Prediction | Libros y Papers sobre  Complejidad - Sistemas Complejos | Scoop.it

Civil unrest is a powerful form of collective human dynamics, which has led to major transitions of societies in modern history. The study of collective human dynamics, including collective aggression, has been the focus of much discussion in the context of modeling and identification of universal patterns of behavior. In contrast, the possibility that civil unrest activities, across countries and over long time periods, are governed by universal mechanisms has not been explored. Here, records of civil unrest of 170 countries during the period 1919–2008 are analyzed. It is demonstrated that the distributions of the number of unrest events per year are robustly reproduced by a nonlinear, spatially extended dynamical model, which reflects the spread of civil disorder between geographic regions connected through social and communication networks. The results also expose the similarity between global social instability and the dynamics of natural hazards and epidemics.

 

 


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Complexity, Selectivity and Asymmetry in the Conformation of the Power Phenomenon. Analysis of Chilean Society

In this work we analyzed the relationships between powerful politicians and businessmen of Chile in order to study the phenomenon of social power. We developed our study according to Complex Network Theory but also using traditional sociological theories of Power and Elites. Our analyses suggest that the studied network displays common properties of Complex Networks, such as scaling in connectivity distribution, properties of small-world networks, and modular structure, among others. We also observed that social power (a proposed metric is presented in this work) is also distributed inhomogeneously. However, the most interesting observation is that this inhomogeneous power and connectivity distribution, among other observed properties, may be the result of a dynamic and unregulated process of network growth in which powerful people tend to link to similar others. The compatibility between people, increasingly selective as the network grows, could generate the presence of extremely powerful people, but also a constant inequality of power where the difference between the most powerful is the same as among the least powerful. Our results are also in accordance with sociological theories.

 

Complexity, Selectivity and Asymmetry in the Conformation of the Power Phenomenon. Analysis of Chilean Society
Juan Pablo Cárdenas, Gerardo Vidal, Gastón Olivares

http://arxiv.org/abs/1409.7862


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On Ethical and Intellectual Failures in Contemporary Economics

Contemporary Anglo-American economics, which I admire, faces two major obstacles. First, in its drive at least since Milton Freedman to be a positive science free of normative issues, it ignores its own current intellectual foundations buried at the heart of its analysis of the “advantages of trade”: Fairness. Second, the major driver of economic growth in the past 50,000 years has been the explosion of goods and production capacities from perhaps 1,000 to 10,000 long ago, to perhaps 10 billion goods and production capacities today. Economics, lacking a theory for this explosion, deals with this explosion by ignoring it and treating it as “exogenous” to its theory.
The “Edgeworth Box” carries the heart of advantages of trade, demonstrating for properly curved isoutility curves a region where you and I are better-off trading some of my apples for some of your pears. The ratio of these in trade constitutes price. But spanning the region of advantages of trade is the famous CONTRACT CURVE, where we have exhausted all the advantages of trade. Different points on the curve correspond to different prices. But the Contract Curve is Pareto Optimal, motion on the curve can only make one of us better-off at the expense of the other. Critically, economics has NO THEORY for where we end up on the Contract Curve. Nor, since different points on the curve correspond to different prices, can PRICE settle the issue.
Using the Ultimatum Game I will show that FAIRNESS typically drives where we settle on the Contract Curve, as long as we do not have to trade with one another. Thus ethics enters economics at its foundation, yet cannot be mathematized, so is ignored in Freedman’s name of a positive science.
Perhaps more important, unlike physics, no laws entail the evolution of either the biosphere or the “econosphere.” There are no laws of motion whose integration would entail that evolution. Lacking an entailing theory of the growth of the economy in diversity, often of new goods and production capacities, economists ignore the most important feature of economic growth, wrongly treating it as “exogenous.”
The failures above are likely to play major roles in the lapse to mere greed in our major financial institutions, and in our inadequate capacities to help drive growth in much of the poverty-struck world.

 

Stuart Kauffman (2014), On Ethical and Intellectual Failures in Contemporary Economics, in Steven Horwitz , Roger Koppl (ed.) Entangled Political Economy (Advances in Austrian Economics, Volume 18) Emerald Group Publishing Limited, pp.259 - 282

 

http://dx.doi.org/10.1108/S1529-213420140000018012


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ECONOMIC NETWORKS: WHAT DO WE KNOW AND WHAT DO WE NEED TO KNOW?

ECONOMIC NETWORKS: WHAT DO WE KNOW AND WHAT DO WE NEED TO KNOW?
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The Fourth Revolution: How the infosphere is reshaping human reality (by Luciano Floridi)

The Fourth Revolution: How the infosphere is reshaping human reality

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Who are we, and how do we relate to each other? Luciano Floridi, one of the leading figures in contemporary philosophy, argues that the explosive developments in Information and Communication Technologies (ICTs) is changing the answer to these fundamental human questions.

As the boundaries between life online and offline break down, and we become seamlessly connected to each other and surrounded by smart, responsive objects, we are all becoming integrated into an "infosphere". Personas we adopt in social media, for example, feed into our 'real' lives so that we begin to live, as Floridi puts in, "onlife". Following those led by Copernicus, Darwin, and Freud, this metaphysical shift represents nothing less than a fourth revolution.

"Onlife" defines more and more of our daily activity - the way we shop, work, learn, care for our health, entertain ourselves, conduct our relationships; the way we interact with the worlds of law, finance, and politics; even the way we conduct war. In every department of life, ICTs have become environmental forces which are creating and transforming our realities. How can we ensure that we shall reap their benefits? What are the implicit risks? Are our technologies going to enable and empower us, or constrain us? Floridi argues that we must expand our ecological and ethical approach to cover both natural and man-made realities, putting the 'e' in an environmentalism that can deal successfully with the new challenges posed by our digital technologies and information society.

 

 


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Aha..... That is Interesting!: John Holland, 85 Years Young (Exploring Complexity): Jan W Vasbinder: 9789814619868: Amazon.com: Books

Aha..... That is Interesting!: John Holland, 85 Years Young (Exploring Complexity)

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Aha..... That is Interesting!: John Holland, 85 Years Young (Exploring Complexity) [Jan W Vasbinder] on Amazon.com. *FREE* shipping on qualifying offers. John Holland is one of the few scientists, who all by themselves and by their pursuits, helped change the course of science and the wealth of human knowledge. There is hardly a field of science or problems
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Data, data everywhere

Data, data everywhere | Libros y Papers sobre  Complejidad - Sistemas Complejos | Scoop.it
All these examples tell the same story: that the world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account.

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Complexity Institute's curator insight, December 28, 2014 9:27 AM

An article dated 2010, but still interesting.

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Revealing Multiple Layers of Hidden Community Structure in Networks

We introduce a new conception of community structure, which we refer to as hidden community structure. Hidden community structure refers to a specific type of overlapping community structure, in which the detection of weak, but meaningful, communities is hindered by the presence of stronger communities. We present Hidden Community Detection HICODE, an algorithm template that identifies both the strong, dominant community structure as well as the weaker, hidden community structure in networks. HICODE begins by first applying an existing community detection algorithm to a network, and then removing the structure of the detected communities from the network. In this way, the structure of the weaker communities becomes visible. Through application of HICODE, we demonstrate that a wide variety of real networks from different domains contain many communities that, though meaningful, are not detected by any of the popular community detection algorithms that we consider. Additionally, on both real and synthetic networks containing a hidden ground-truth community structure, HICODE uncovers this structure better than any baseline algorithms that we compared against. For example, on a real network of undergraduate students that can be partitioned either by `Dorm' (residence hall) or `Year', we see that HICODE uncovers the weaker `Year' communities with a JCRecall score (a recall-based metric that we define in the text) of over 0.7, while the baseline algorithms achieve scores below 0.2.

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Dynamical Response of Networks Under External Perturbations: Exact Results | NECSI

Abstract

We give exact statistical distributions for the dynamic response of influence networks subjected to external perturbations. We consider networks whose nodes have two internal states labeled 0 and 1. We let N0 nodes be frozen in state 0, N1 in state 1, and the remaining nodes change by adopting the state of a connected node with a fixed probability per time step. The frozen nodes can be interpreted as external perturbations to the subnetwork of free nodes. Analytically extending N0 and N1 to be smaller than 1 enables modeling the case of weak coupling. We solve the dynamical equations exactly for fully connected networks, obtaining the equilibrium distribution, transition probabilities between any two states and the characteristic time to equilibration. Our exact results are excellent approximations for other topologies, including random, regular lattice, scale-free and small world networks, when the numbers of fixed nodes are adjusted to take account of the effect of topology on coupling to the environment. This model can describe a variety of complex systems, from magnetic spins to social networks to population genetics, and was recently applied as a framework for early warning signals for real-world self-organized economic market crises.
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NECSI paper published with exact results for network model used to predict market crashes

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Collective behaviors and networks

The goal of this thematic series is to provide a discussion venue about recent advances in the study of networks and their applications to the study of collective behavior in socio-technical systems. The series includes contributions exploring the intersection between data-driven studies of complex networks and agent-based models of collective social behavior. Particular attention is devoted to topics aimed at understanding social behavior through the lens of data about technology-mediated communication. These include: modeling social dynamics of attention and collaboration, characterizing online group formation and evolution, and studying the emergence of roles and interaction patterns in social media environments.

 

Collective behaviors and networks
Giovanni Luca Ciampaglia, Emilio Ferrara and Alessandro Flammini

EPJ Data Science 2014, 3:37  http://dx.doi.org/10.1140/epjds/s13688-014-0037-6


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The Information Theory of Individuality

We consider biological individuality in terms of information theoretic and graphical principles. Our purpose is to extract through an algorithmic decomposition system-environment boundaries supporting individuality. We infer or detect evolved individuals rather than assume that they exist. Given a set of consistent measurements over time, we discover a coarse-grained or quantized description on a system, inducing partitions (which can be nested). Legitimate individual partitions will propagate information from the past into the future, whereas spurious aggregations will not. Individuals are therefore defined in terms of ongoing, bounded information processing units rather than lists of static features or conventional replication-based definitions which tend to fail in the case of cultural change. One virtue of this approach is that it could expand the scope of what we consider adaptive or biological phenomena, particularly in the microscopic and macroscopic regimes of molecular and social phenomena.

 

The Information Theory of Individuality
David Krakauer, Nils Bertschinger, Eckehard Olbrich, Nihat Ay, Jessica C. Flack

http://arxiv.org/abs/1412.2447


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How Do Agents Make Decisions?

When designing an agent-based simulation, an important question to answer is how to model the decision making processes of the agents in the system. A large number of agent decision making models can be found in the literature, each inspired by different aims and research questions. In this paper we provide a review of 14 agent decision making architectures that have attracted interest. They range from production-rule systems to psychologically- and neurologically-inspired approaches. For each of the architectures we give an overview of its design, highlight research questions that have been answered with its help and outline the reasons for the choice of the decision making model provided by the originators. Our goal is to provide guidelines about what kind of agent decision making model, with which level of simplicity or complexity, to use for which kind of research question.by Tina Balke and Nigel Gilbert


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Lorien Pratt's curator insight, November 12, 2014 2:13 PM

For those note familiar with agent-based social simulation, the idea is to simulate the individual decisions of many "agents", each representing a person, in some situation.  For example, we might model decisions that people make as they move through a train station or amusement park, in order to design those places to best handle traffic flow. 


This is a terrific, comprehensive review article, covering a number of ways of approaching the task of modeling those individual decisions made by simulated agents.  Each is designed with somewhat different constraints in mind.  For instance, some models like SOAR, are meant to mimic certain cognitive processes.


From a Decision Intelligence point of view, these approaches are complementary.  If we want a sophisticated model of the emergent behavior of a large number of people, as one building block in a decision model for what to do about it, an agent-based simulation can be very helpful. For instance, we might be trying to decide which new medicine to launch, taking into account our competitors, our price to produce the medicine, and its impact on disease.  Part of that decision model might be based on an agent-based simulation of the decisions that people make to take the medicine, and their behavior that leads to contracting the disease. 


To continue the example, we could either use an agent-based simulation to learn from the agent-based simulation, or have it run in the same simulation as a decision model. For an example of the first, an agent-based simulation might show that the disease is expected to grow geographically according to a certain pattern. That spread pattern would then be an external input to a decision model. 


The second way to use this is to use the decision model to interactively move certain assumptions about the decision-making process, and to immediately observe the impact on agents. For instance, we may adjust the number of dollars invested in a public health campaign and observe how that impacts the emergent properties of an agent-based simulation.  There are a lot of possibilities here!



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Modeling Social Dynamics in a Collaborative Environment

Wikipedia is a prime example of today's value production in a collaborative environment. Using this example, we model the emergence, persistence and resolution of severe conflicts during collaboration by coupling opinion formation with article editing in a bounded confidence dynamics. The complex social behavior involved in editing articles is implemented as a minimal model with two basic elements; (i) individuals interact directly to share information and convince each other, and (ii) they edit a common medium to establish their own opinions. Opinions of the editors and that represented by the article are characterised by a scalar variable. When the pool of editors is fixed, three regimes can be distinguished: (a) a stable mainstream article opinion is continuously contested by editors with extremist views and there is slow convergence towards consensus, (b) the article oscillates between editors with extremist views, reaching consensus relatively fast at one of the extremes, and (c) the extremist editors are converted very fast to the mainstream opinion and the article has an erratic evolution. When editors are renewed with a certain rate, a dynamical transition occurs between different kinds of edit wars, which qualitatively reflect the dynamics of conflicts as observed in real Wikipedia data.


Modeling Social Dynamics in a Collaborative Environment

Gerardo Iñiguez, János Török, Taha Yasseri, Kimmo Kaski, János Kertész

http://arxiv.org/abs/1403.3568


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Double Percolation Phase Transition in Clustered Complex Networks

Double Percolation Phase Transition in Clustered Complex Networks | Libros y Papers sobre  Complejidad - Sistemas Complejos | Scoop.it

The percolation properties of networks are strongly affected by their topological features. A new study shows that percolation can proceed at different rates in the core and periphery of a complex, clustered network.

 

 

Double Percolation Phase Transition in Clustered Complex Networks
Pol Colomer-de-Simón and Marián Boguñá
Phys. Rev. X 4, 041020 (2014)

http://dx.doi.org/10.1103/PhysRevX.4.041020


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Economics in the age of big data

The advent of big data is already allowing for better measurement of economic effects and outcomes and is enabling novel research designs across a range of topics. Over time, these data are likely to affect the types of questions economists pose, by allowing for more focus on population variation and the analysis of a broader range of economic activities and interactions. We also expect economists to increasingly adopt the large-data statistical methods that have been developed in neighboring fields and that often may complement traditional econometric techniques.
These data opportunities also raise some important challenges. Perhaps the primary one is developing methods for researchers to access and explore data in ways that respect privacy and confidentiality concerns. This is a major issue in working with both government administrative data and private sector firms. Other challenges include developing the appropriate data management and programming capabilities, as well as designing creative and scalable approaches to summarize, describe, and analyze large-scale and relatively unstructured data sets. These challenges notwithstanding, the next few decades are likely to be a very exciting time for economic research.

 

Economics in the age of big data

Liran Einav, Jonathan Levin

 

Science 7 November 2014:
Vol. 346 no. 6210
http://dx.doi.org/10.1126/science.1243089


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A typology of street patterns

We propose a quantitative method to classify cities according to their street pattern. We use the conditional probability distribution of shape factor of blocks with a given area and define what could constitute the ‘fingerprint’ of a city. Using a simple hierarchical clustering method, these fingerprints can then serve as a basis for a typology of cities. We apply this method to a set of 131 cities in the world, and at an intermediate level of the dendrogram, we observe four large families of cities characterized by different abundances of blocks of a certain area and shape. At a lower level of the classification, we find that most European cities and American cities in our sample fall in their own sub-category, highlighting quantitatively the differences between the typical layouts of cities in both regions. We also show with the example of New York and its different boroughs, that the fingerprint of a city can be seen as the sum of the ones characterizing the different neighbourhoods inside a city. This method provides a quantitative comparison of urban street patterns, which could be helpful for a better understanding of the causes and mechanisms behind their distinct shapes.

 

A typology of street patterns
Rémi Louf, Marc Barthelemy

http://dx.doi.org/10.1098/rsif.2014.0924

J. R. Soc. Interface 6 December 2014 vol. 11 no. 101 20140924

Also at http://arxiv.org/abs/1410.2094


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EMERGENCE OF POWER-LAW AND TWO-PHASE BEHAVIOR IN FINANCIAL MARKET FLUCTUATIONS

EMERGENCE OF POWER-LAW AND TWO-PHASE BEHAVIOR IN FINANCIAL MARKET FLUCTUATIONS | Libros y Papers sobre  Complejidad - Sistemas Complejos | Scoop.it
ZVONKO KOSTANJČAR and BRANKO JEREN, Advs. Complex Syst. 16, 1350008 (2013) [12 pages] DOI: 10.1142/S0219525913500082
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