Papers by Luis Bettencourt
European Journal of Archaeology, Nov 13, 2023
Reductions in the cost of transporting manufactured goods have been an important element in econo... more Reductions in the cost of transporting manufactured goods have been an important element in economic development in the recent past, and previous research suggests that the Roman period in Britain also saw substantial reductions in such costs. The authors investigate how far it is possible to measure changes in transport costs by considering the spatial distributions of pottery from known Roman production locations over time. Their analysis of an extensive database of pottery assemblages is designed to evaluate a series of expectations concerning how reductions in transport costs may have affected such assemblages and their distribution. Results suggest that costs were reduced by a factor of about two, leading to related changes in pottery production, distribution, and consumption over time. The ability to quantify changes in transport costs opens new perspectives for investigating the general determinants of economic development using archaeological data.
arXiv (Cornell University), Dec 11, 2002
Social trends or fashions are spontaneous collective decisions made by large portions of a commun... more Social trends or fashions are spontaneous collective decisions made by large portions of a community, often without an apparent good reason. The spontaneous formation of trends provides a well documented mechanism for the spread of information across a population, the creation of culture and the self-regulation of social behavior. Here I introduce an agent based dynamical model that captures the essence of trend formation and collapse. The resulting population dynamics alternates states of great diversity (large configurational entropy) with the dominance by a few trends. This behavior displays a kind of self-organized criticality, measurable through cumulants analogous to those used to study percolation. I also analyze the robustness of trend dynamics subject to external influences, such as population growth or contraction and in the presence of explicit information biases. The resulting population response gives insights about the fragility of public opinion in specific circumstances and suggests how it may be driven to produce social consensus or dissonance.
The urban book series, 2021
Many forms of ambient data in cities are starting to become available that allows tracking of sho... more Many forms of ambient data in cities are starting to become available that allows tracking of short-term urban operations, such as traffic management, trash collections, inspections, or non-emergency maintenance requests. However, arguably the greatest promise of urban analytics is to set up measurable objectives and track progress toward systemic development goals connected to human development and sustainability over the longer term. The challenge for such an approach is the connection between new technological capabilities, such as sensing and machine learning and local knowledge, and operations of residents and city governments. Here, we describe an emerging project for the long-term monitoring of sustainable development in fast-growing towns in the Galapagos Islands through the convergence of these methods. We demonstrate how collaborative mapping and the capture of 360-degree street views can produce a general basis for a broad set of quantitative analytics, when such actions are coupled to mapping and deep-learning characterizations of urban environments. We map and assess the precision of urban assets via automatic object classification and characterize their abundance and spatial heterogeneity. We also discuss how these methods, as they continue to improve, can provide the means to perform an ambient census of urban assets (buildings, vehicles, services) and environmental conditions.
Conference on Email and Anti-Spam, 2005
Email is an increasingly important and ubiquitous means of communication, both facilitating conta... more Email is an increasingly important and ubiquitous means of communication, both facilitating contact between individuals and enabling rises in the productivity of organizations. However, the relentless rise of automatic unauthorized emails, a.k.a. spam is eroding away much of the attractiveness of email communication. Most of the attention dedicated to spam detection has focused on the content of the emails or on the addresses or domains associated with spam senders. Although, methods based on these -easily changeable -identifiers work reasonably well, they miss on the fundamental nature of spam as an opportunistic relationship, very different from the normal mutual relations between senders and recipients of legitimate email. Here we present a comprehensive graph theoretical analysis of email traffic that captures these properties quantitatively. We identify several simple metrics that serve both to distinguish between spam and legitimate email and to provide a statistical basis for models of spam traffic.
npj Urban Sustainability, Feb 20, 2023
Human development is a complex process involving interactions between individuals and their socio... more Human development is a complex process involving interactions between individuals and their socioeconomic, biological, and physical environments. It has been studied using two frameworks: the "Capabilities Approach," implemented at the national scale, and the "Neighborhood Effects Approach," implemented at the community scale. However, no existing framework conceptualizes and measures human development across geographic scales. Here, we unite the two approaches by localizing the Human Development Index (HDI), and demonstrate a methodology for scalable implementation of this index for comparative analysis. We analyzed patterns of development in the United States, characterizing over 70,000 communities. We found that, on average, larger cities have higher HDI (higher standard of living) but exhibit greater disparities between communities, and that increases in community HDI are associated with the simultaneous reduction of a diverse set of negative neighborhood effects. Our framework produces an interdisciplinary synthesis of theory and practice for sustainable, equitable urban health and development.
arXiv (Cornell University), Oct 3, 2015
Over the last decades, in disciplines as diverse as economics, geography, and complex systems, a ... more 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.
arXiv (Cornell University), Apr 14, 2020
We consider a single outbreak susceptible-infected-recovered (SIR) model and corresponding estima... more We consider a single outbreak susceptible-infected-recovered (SIR) model and corresponding estimation procedures for the effective reproductive number R(t). We discuss the estimation of the underlying SIR parameters with a generalized least squares (GLS) estimation technique. We do this in the context of appropriate statistical models for the measurement process. We use asymptotic statistical theories to derive the mean and variance of the limiting (Gaussian) sampling distribution and to perform post statistical analysis of the inverse problems. We illustrate the ideas and pitfalls (e.g., large condition numbers on the corresponding Fisher information matrix) with both synthetic and influenza incidence data sets.
EPJ Data Science, Sep 3, 2022
Cities have been extensively studied as complex adaptive systems over the last 50 years. Recently... more Cities have been extensively studied as complex adaptive systems over the last 50 years. Recently, several empirical studies and emerging theory provided support for the fact that many different urban indicators follow general consistent statistical patterns across countries, cultures and times. In particular, total personal income, measures of innovation, crime rates, characteristics of the built environment and other indicators have been shown to exhibit non-linear power-law scaling with the population size of functional cities. Here, we show how to apply this type of analysis inside cities to establish universal patterns in the quantity and distribution of urban amenities such as restaurants, parks, and universities. Using a unique data set containing millions of amenities in the 50 largest US metropolitan areas, we establish general non-linear scaling patterns between each city's population and many different amenities types, the small-area statistics of their spatial abundance, and the characteristics of their mean distance to each other. We use these size-specific statistical findings to produce generative models for the expected amenity abundances of any US city. We then compute the deviations observed in given cities from this statistical many-amenity model to build a characteristic signature for each urban area. Finally, we show how urban planning can be guided by these systemic quantitative expectations in the context of new city design or the identification of local deficits in service provision in existing cities.
arXiv (Cornell University), Dec 6, 2022
Homophily and heterophobia, the tendency for people with similar characteristics to preferentiall... more Homophily and heterophobia, the tendency for people with similar characteristics to preferentially interact with (or avoid) each other are pervasive in human social networks. Here, we develop an extension of the mathematical theory of urban scaling which describes the effects of homophily and heterophobia on social interactions and resulting economic outputs of cities. Empirical tests of our model show that increased residential racial heterophobia and segregation in U.S. cities are associated with reduced economic outputs and that the strength of this relationship increased throughout the 2010s. Our findings provide the means for the formal incorporation of general homophilic and heterophobic effects into theories of modern urban science and suggest 1
Nuclear physics, May 1, 2003
arXiv (Cornell University), Apr 14, 2003
Recent progress in the large scale mapping of social networks is opening new quantitative windows... more Recent progress in the large scale mapping of social networks is opening new quantitative windows into the structure of human societies. These networks are largely the result of how we access and utilize information. Here I show that a universal decision mechanism, where we base our choices on the actions of others, can explain much of their structure. Such collective social arrangements emerge from successful strategies to handle information flow at the individual level. They include the formation of closely-knit communities and the emergence of well-connected individuals. The latter can command the following of others while only exercising ordinary judgment.
Physical review, Aug 27, 2001
O(N ) symmetric λφ 4 field theories describe many critical phenomena in the laboratory and in the... more O(N ) symmetric λφ 4 field theories describe many critical phenomena in the laboratory and in the early Universe. Given N and D ≤ 3, the dimension of space, these models exhibit topological defect classical solutions that in some cases fully determine their critical behavior. For N = 2, D = 3 it has been observed that the defect density is seemingly a universal quantity at Tc. We prove this conjecture and show how to predict its value based on the universal critical exponents of the field theory. Analogously, for general N and D we predict the universal critical densities of domain walls and monopoles, for which no detailed thermodynamic study exists. This procedure can also be inverted, producing an algorithm for generating typical defect networks at criticality, in contrast to the canonical procedure [1], which applies only in the unphysical limit of infinite temperature.
Physical review, Jun 21, 2002
We determine the detailed thermodynamic behavior of vortices in the O(2) scalar model in 2D and o... more We determine the detailed thermodynamic behavior of vortices in the O(2) scalar model in 2D and of global monopoles in the O(3) model in 3D. We construct new numerical techniques, based on cluster decomposition algorithms, to analyze the point defect configurations. We find that these criteria produce results for the Kosterlitz-Thouless temperature in agreement with a topological transition between a polarizable insulator and a conductor, at which free topological charges appear in the system. For global monopoles we find no pair unbinding transition. Instead a transition to a dense state where pairs are no longer distinguishable occurs at T < Tc, without leading to long range disorder. We produce both extensive numerical evidence of this behavior as well as a semi-analytic treatment of the partition function for defects. General expectations for N = D > 3 are drawn, based on the observed behavior.
PLOS ONE, Sep 3, 2019
Nowhere has the scale and scope of urbanization been larger than in China over the last few decad... more Nowhere has the scale and scope of urbanization been larger than in China over the last few decades. We analyze Chinese city development between the years 1996 and 2014 using data for the urbanized components of prefecture-level cities. We show that, despite much variability and fast economic and demographic change, China is undergoing transformations similar to the historical trajectory of other urban systems. We also show that the distinguishing signs of urban economies-superlinear scaling of agglomeration effects in economic productivity and economies of scale in land use-also characterize Chinese cities. We then analyze the structure of economic change in Chinese cities using a variety of metrics, characterizing employment, firms and households. Population size estimates remain a major challenge for Chinese cities, as official numbers are often reported based on the Hukou registration system. We use the information in the residuals to scaling relations for economic quantities to predict actual resident population and show that these estimates agree well with data for a subset of cities for which counts of total resident population exist. We conclude with a list of issues that must be better understood and measured to make sense of present urban development trajectories in China.
Implicit biases, expressed as differential treatment towards out-group members, are pervasive in ... more Implicit biases, expressed as differential treatment towards out-group members, are pervasive in human societies. These biases are often racial or ethnic in nature and create disparities and inequities across many aspects of life. Recent research has revealed that implicit biases are, for the most part, driven by social contexts and local histories. However, it has remained unclear how and if the regular ways in which human societies self-organize in cities produce systematic variation in implicit bias strength. Here we leverage extensions of the mathematical models of urban scaling theory to predict and test between-city differences in implicit racial biases. Our model comprehensively links scales of organization from city-wide infrastructure to individual psychology to quanti-tatively predict that cities that are (1) more populous, (2) more diverse, and (3) less segregated have lower levels of implicit biases. We find broad empirical support for each of these predictions in U.S. cities for data spanning a decade of racial implicit association tests from millions of individuals. We conclude that the organization of cities strongly drives the strength of implicit racial biases and provides potential systematic intervention targets for the development and planning of more equitable societies.
arXiv (Cornell University), Mar 17, 2011
A convolution model which accounts for neural activity dynamics in the primary visual cortex is d... more A convolution model which accounts for neural activity dynamics in the primary visual cortex is derived and used to detect visually salient contours in images. Image inputs to the model are modulated by long-range horizontal connections, allowing contextual effects in the image to determine visual saliency, i.e. line segments arranged in a closed contour elicit a larger neural response than line segments forming background clutter. The model is tested on 3 types of contour, including a line, a circular closed contour, and a non-circular closed contour. Using a modified association field to describe horizontal connections the model is found to perform well for different parameter values. For each type of contour a different facilitation mechanism is found. Operating as a feed-forward network, the model assigns saliency by increasing the neural activity of line segments facilitated by the horizontal connections. Alternatively, operating as a feedback network, the model can achieve further improvement over several iterations through cooperative interactions. This model has no dynamical stability issues, and is suitable for use in biologically-inspired neural networks.
PNAS nexus, Mar 22, 2023
Stochastic multiplicative dynamics characterize many complex natural phenomena such as selection ... more Stochastic multiplicative dynamics characterize many complex natural phenomena such as selection and mutation in evolving populations, and the generation and distribution of wealth within social systems. Population heterogeneity in stochastic growth rates has been shown to be the critical driver of wealth inequality over long time scales. However, we still lack a general statistical theory that systematically explains the origins of these heterogeneities resulting from the dynamical adaptation of agents to their environment. In this paper, we derive population growth parameters resulting from the general interaction between agents and their environment, conditional on subjective signals each agent perceives. We show that average wealth growth rates converge, under specific conditions, to their maximal value as the mutual information between the agent's signal and the environment, and that sequential Bayesian inference is the optimal strategy for reaching this maximum. It follows that when all agents access the same statistical environment, the learning process attenuates growth rate disparities, reducing the long-term effects of heterogeneity on inequality. Our approach shows how the formal properties of information underlie general growth dynamics across social and biological phenomena, including cooperation and the effects of education and learning on life history choices.
arXiv (Cornell University), Sep 20, 2022
Stochastic multiplicative dynamics characterize many complex natural phenomena such as selection ... more Stochastic multiplicative dynamics characterize many complex natural phenomena such as selection and mutation in evolving populations, and the generation and distribution of wealth within social systems. Population heterogeneity in stochastic growth rates has been shown to be the critical driver of diversity dynamics and of the emergence of wealth inequality over long time scales. However, we still lack a general statistical framework that systematically explains the origins of these heterogeneities from the adaptation of agents to their environment. In this paper, we derive population growth parameters resulting from the interaction between agents and their knowable environment, conditional on subjective signals each agent receives. We show that average growth rates converge, under specific conditions, to their maximal value as the mutual information between the agent's signal and the environment, and that sequential Bayesian inference is the optimal strategy for reaching this maximum. It follows that when all agents access the same environment using the same inference model, the learning process dynamically attenuates growth rate disparities, reversing the long-term effects of heterogeneity on inequality. Our approach lays the foundation for a unified general quantitative modeling of social and biological phenomena such as the dynamical effects of cooperation, and the effects of education on life history choices.
Physica D: Nonlinear Phenomena, Dec 1, 2022
Understanding the statistical dynamics of growth and inequality is a fundamental challenge to eco... more Understanding the statistical dynamics of growth and inequality is a fundamental challenge to ecology and society. Recent analyses of wealth and income dynamics in contemporary societies show that economic inequality is very dynamic and that individuals experience substantially different growth rates over time. However, despite a fast growing body of evidence for the importance of fluctuations, we still lack a general statistical theory for understanding the dynamical effects of heterogeneneous growth across a population. Here we derive the statistical dynamics of correlated growth rates in heterogeneous populations. We show that correlations between growth rate fluctuations at the individual level influence aggregate population growth, while only driving inequality on short time scales. We also find that growth rate fluctuations are a much stronger driver of longterm inequality than earnings volatility. Our findings show that the dynamical effects of statistical fluctuations in growth rates are critical for understanding the emergence of inequality over time and motivate a greater focus on the properties and endogenous origins of growth rates in stochastic environments.
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Papers by Luis Bettencourt