M. E. J. Newman
- Published in print:
- 2010
- Published Online:
- September 2010
- ISBN:
- 9780199206650
- eISBN:
- 9780191594175
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199206650.003.0018
- Subject:
- Physics, Theoretical, Computational, and Statistical Physics
Many real-world processes — or simplified models of real-world processes — can be represented as dynamical systems on networks. The spread of news or information between friends, the movement of ...
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Many real-world processes — or simplified models of real-world processes — can be represented as dynamical systems on networks. The spread of news or information between friends, the movement of money through an economy, the flow of traffic on roads, data over the Internet, or electricity over the grid, the evolution of populations in an ecosystem, the changing concentrations of metabolites in a cell, and many other systems of scientific interest are best thought of as dynamical processes of one kind or another taking place on an appropriate network. In other, non-network contexts, the theory of dynamical systems is a well-developed branch of mathematics and physics. This chapter delves into some of this theory and shows how it can be applied to dynamical systems on networks. It focuses on deterministic systems of continuous real-valued variables evolving in continuous time t. Exercises are provided at the end of the chapter.Less
Many real-world processes — or simplified models of real-world processes — can be represented as dynamical systems on networks. The spread of news or information between friends, the movement of money through an economy, the flow of traffic on roads, data over the Internet, or electricity over the grid, the evolution of populations in an ecosystem, the changing concentrations of metabolites in a cell, and many other systems of scientific interest are best thought of as dynamical processes of one kind or another taking place on an appropriate network. In other, non-network contexts, the theory of dynamical systems is a well-developed branch of mathematics and physics. This chapter delves into some of this theory and shows how it can be applied to dynamical systems on networks. It focuses on deterministic systems of continuous real-valued variables evolving in continuous time t. Exercises are provided at the end of the chapter.
James Moody and Dana K. Pasquale
- Published in print:
- 2020
- Published Online:
- July 2020
- ISBN:
- 9780190880743
- eISBN:
- 9780190880774
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780190880743.003.0004
- Subject:
- Public Health and Epidemiology, Public Health, Epidemiology
People constantly interact with each other and their environment, and these interactions—with whom and with what they interact—are not random. Interactions at multiple levels (cellular, neurological, ...
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People constantly interact with each other and their environment, and these interactions—with whom and with what they interact—are not random. Interactions at multiple levels (cellular, neurological, social, physical, environmental) shape one’s experiences and affect health and well-being. These interactions can be represented as a set of networks that feedback and influence other networks. Here we limit our scope to the complex relationship between human social networks and behavior, which frequently forms a feedback loop, and the effect of this relationship on population health outcomes. This chapter introduces traditional network analysis as it pertains to population health, explores examples of interactions between macro-level networks, and proposes future directions for network analysisLess
People constantly interact with each other and their environment, and these interactions—with whom and with what they interact—are not random. Interactions at multiple levels (cellular, neurological, social, physical, environmental) shape one’s experiences and affect health and well-being. These interactions can be represented as a set of networks that feedback and influence other networks. Here we limit our scope to the complex relationship between human social networks and behavior, which frequently forms a feedback loop, and the effect of this relationship on population health outcomes. This chapter introduces traditional network analysis as it pertains to population health, explores examples of interactions between macro-level networks, and proposes future directions for network analysis
Ginestra Bianconi
- Published in print:
- 2018
- Published Online:
- July 2018
- ISBN:
- 9780198753919
- eISBN:
- 9780191815676
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780198753919.001.0001
- Subject:
- Physics, Theoretical, Computational, and Statistical Physics
Multilayer networks are formed by several networks that interact with each other and co-evolve. Multilayer networks include social networks, financial markets, transportation systems, infrastructures ...
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Multilayer networks are formed by several networks that interact with each other and co-evolve. Multilayer networks include social networks, financial markets, transportation systems, infrastructures and molecular networks and the brain. The multilayer structure of these networks strongly affects the properties of dynamical and stochastic processes defined on them, which can display unexpected characteristics. For example, interdependencies between different networks of a multilayer structure can cause cascades of failure events that can dramatically increase the fragility of these systems; spreading of diseases, opinions and ideas might take advantage of multilayer network topology and spread even when its single layers cannot sustain an epidemic when taken in isolation; diffusion on multilayer transportation networks can significantly speed up with respect to diffusion on single layers; finally, the interplay between multiplexity and controllability of multilayer networks is a problem with major consequences in financial, transportation, molecular biology and brain networks. This field is one of the most prosperous recent developments of Network Science and Data Science. Multilayer networks include multiplex networks, multi-slice temporal networks, networks of networks, interdependent networks. Multilayer networks are characterized by having a highly correlated multilayer network structure, providing a significant advantage for extracting information from them using multilayer network measures and centralities and community detection methods. The multilayer network dynamics (including percolation, epidemic spreading, diffusion, synchronization, game theory and control) is strongly affected by the multilayer network topology. This book will present a comprehensive account of this emerging field.Less
Multilayer networks are formed by several networks that interact with each other and co-evolve. Multilayer networks include social networks, financial markets, transportation systems, infrastructures and molecular networks and the brain. The multilayer structure of these networks strongly affects the properties of dynamical and stochastic processes defined on them, which can display unexpected characteristics. For example, interdependencies between different networks of a multilayer structure can cause cascades of failure events that can dramatically increase the fragility of these systems; spreading of diseases, opinions and ideas might take advantage of multilayer network topology and spread even when its single layers cannot sustain an epidemic when taken in isolation; diffusion on multilayer transportation networks can significantly speed up with respect to diffusion on single layers; finally, the interplay between multiplexity and controllability of multilayer networks is a problem with major consequences in financial, transportation, molecular biology and brain networks. This field is one of the most prosperous recent developments of Network Science and Data Science. Multilayer networks include multiplex networks, multi-slice temporal networks, networks of networks, interdependent networks. Multilayer networks are characterized by having a highly correlated multilayer network structure, providing a significant advantage for extracting information from them using multilayer network measures and centralities and community detection methods. The multilayer network dynamics (including percolation, epidemic spreading, diffusion, synchronization, game theory and control) is strongly affected by the multilayer network topology. This book will present a comprehensive account of this emerging field.
Sonia Kéfi
- Published in print:
- 2020
- Published Online:
- July 2020
- ISBN:
- 9780198824282
- eISBN:
- 9780191863271
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780198824282.003.0010
- Subject:
- Biology, Ecology, Biomathematics / Statistics and Data Analysis / Complexity Studies
Ecological systems are undeniably complex, including many species interacting in different ways with each other (e.g., predation, competition, facilitation, parasitism). One way of visualizing, ...
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Ecological systems are undeniably complex, including many species interacting in different ways with each other (e.g., predation, competition, facilitation, parasitism). One way of visualizing, describing, and studying this complexity is to represent them as networks, where nodes are typically species and links are interactions between these species. The study of these networks allows understanding of the rules governing the topology of their links, and assessing how network structure drives ecological dynamics. Studies on different types of ecological networks have suggested that they exhibit structural regularities, which in turn affect network dynamics and resilience to perturbations. Although the use of networks to represent ecological communities dates back to the early stages of the discipline, the last two decades have seen rapid progresses in our understanding of ecological networks, as data are collected at a faster rate and better resolution, as metrics are continuously developed to better characterize network structure and as numerical simulations of mathematical models have allowed investigating how network structure and dynamics are related in more comprehensive and realistic ecological networks. This chapter describes some of the recent developments and challenges related to the study of ecological networks. After defining networks in general, and ecological networks more specifically, recent results regarding the structure of different types of ecological networks, and what is known about their dynamics and resilience, are presented.Less
Ecological systems are undeniably complex, including many species interacting in different ways with each other (e.g., predation, competition, facilitation, parasitism). One way of visualizing, describing, and studying this complexity is to represent them as networks, where nodes are typically species and links are interactions between these species. The study of these networks allows understanding of the rules governing the topology of their links, and assessing how network structure drives ecological dynamics. Studies on different types of ecological networks have suggested that they exhibit structural regularities, which in turn affect network dynamics and resilience to perturbations. Although the use of networks to represent ecological communities dates back to the early stages of the discipline, the last two decades have seen rapid progresses in our understanding of ecological networks, as data are collected at a faster rate and better resolution, as metrics are continuously developed to better characterize network structure and as numerical simulations of mathematical models have allowed investigating how network structure and dynamics are related in more comprehensive and realistic ecological networks. This chapter describes some of the recent developments and challenges related to the study of ecological networks. After defining networks in general, and ecological networks more specifically, recent results regarding the structure of different types of ecological networks, and what is known about their dynamics and resilience, are presented.
Ginestra Bianconi
- Published in print:
- 2018
- Published Online:
- July 2018
- ISBN:
- 9780198753919
- eISBN:
- 9780191815676
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780198753919.003.0003
- Subject:
- Physics, Theoretical, Computational, and Statistical Physics
This chapter provides the relevant background on the network dynamics of complex networks formed by just one layer (single networks). Emergent properties of network dynamics are characterized using ...
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This chapter provides the relevant background on the network dynamics of complex networks formed by just one layer (single networks). Emergent properties of network dynamics are characterized using the framework of phase transitions. The major results on robustness of complex networks, percolation theory and epidemic spreading are presented, revealing the rich interplay between network structure and function. In this context particular emphasis is given to the implications of the scale-free network topology on these dynamical processes. Diffusion processes and synchronization and controllability are characterized on networks, revealing the relevance of spectral properties and peripheral nodes for determining their dynamical behaviour.Less
This chapter provides the relevant background on the network dynamics of complex networks formed by just one layer (single networks). Emergent properties of network dynamics are characterized using the framework of phase transitions. The major results on robustness of complex networks, percolation theory and epidemic spreading are presented, revealing the rich interplay between network structure and function. In this context particular emphasis is given to the implications of the scale-free network topology on these dynamical processes. Diffusion processes and synchronization and controllability are characterized on networks, revealing the relevance of spectral properties and peripheral nodes for determining their dynamical behaviour.
David Lazer
- Published in print:
- 2012
- Published Online:
- January 2013
- ISBN:
- 9780195371895
- eISBN:
- 9780199979127
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780195371895.003.0009
- Subject:
- Political Science, Democratization
In Chapter 9, political scientist and scholar of social networks David Lazer gives an overview of the standard tools of social network analysis. He explains how network dynamics can be useful for ...
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In Chapter 9, political scientist and scholar of social networks David Lazer gives an overview of the standard tools of social network analysis. He explains how network dynamics can be useful for understanding human rights issues as they relate to global flows of people, information and goods, as well as for understanding the relationships between states and sub-state actors within the human rights regime.Less
In Chapter 9, political scientist and scholar of social networks David Lazer gives an overview of the standard tools of social network analysis. He explains how network dynamics can be useful for understanding human rights issues as they relate to global flows of people, information and goods, as well as for understanding the relationships between states and sub-state actors within the human rights regime.
Barbara J. Mills, John M. Roberts Jr., Jeffery J. Clark, William R. Haas Jr., Deborah Huntley, Matthew A. Peeples, Lewis Borck, Susan C. Ryan, Meaghan Trowbridge, and Ronald L. Breiger
- Published in print:
- 2013
- Published Online:
- May 2013
- ISBN:
- 9780199697090
- eISBN:
- 9780191745300
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780199697090.003.0008
- Subject:
- Classical Studies, Archaeology: Classical
This chapter conducts social network analysis on two case studies from the late prehispanic US Southwest. It takes a diachronic perspective in order to look at network dynamics over a 200-year period ...
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This chapter conducts social network analysis on two case studies from the late prehispanic US Southwest. It takes a diachronic perspective in order to look at network dynamics over a 200-year period (ad 1200 to 1400). The case studies chosen are areas where, through independent data, extensive migration has been demonstrated and is widely accepted. The analyses pertain to three specific topics of archaeological interest: (1) first-comer advantage within a social landscape of migration; (2) the relationship of spatial to social centrality; and (3) node persistence or resilience over time. The chapter focuses on two geographically circumscribed areas of central and south-eastern Arizona — the San Pedro Valley and the Tonto Basin — which have been intensively studied by archaeologists over the past two decades. Although both areas saw periods of migration, the outcomes were very different. Because of the temporal control allowed by decades of archaeological research in the south-west, including tree-ring dating, the 200-year time span could be divided into 50-year ‘snapshots’ to look at changes over time.Less
This chapter conducts social network analysis on two case studies from the late prehispanic US Southwest. It takes a diachronic perspective in order to look at network dynamics over a 200-year period (ad 1200 to 1400). The case studies chosen are areas where, through independent data, extensive migration has been demonstrated and is widely accepted. The analyses pertain to three specific topics of archaeological interest: (1) first-comer advantage within a social landscape of migration; (2) the relationship of spatial to social centrality; and (3) node persistence or resilience over time. The chapter focuses on two geographically circumscribed areas of central and south-eastern Arizona — the San Pedro Valley and the Tonto Basin — which have been intensively studied by archaeologists over the past two decades. Although both areas saw periods of migration, the outcomes were very different. Because of the temporal control allowed by decades of archaeological research in the south-west, including tree-ring dating, the 200-year time span could be divided into 50-year ‘snapshots’ to look at changes over time.
István Czachesz
- Published in print:
- 2017
- Published Online:
- January 2017
- ISBN:
- 9780198779865
- eISBN:
- 9780191825880
- Item type:
- book
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:oso/9780198779865.001.0001
- Subject:
- Religion, Biblical Studies, Religious Studies
This monograph makes a case for a cognitive turn in New Testament Studies, both surveying relevant developments in the Cognitive Science of Religion and digging into the field of cognitive and ...
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This monograph makes a case for a cognitive turn in New Testament Studies, both surveying relevant developments in the Cognitive Science of Religion and digging into the field of cognitive and behavioral sciences in search of opportunities of gaining new insights about biblical materials. Over the last few decades, our knowledge of how the human mind and brain work increased dramatically. We can now understand religious traditions, rituals, and visionary experiences in novel ways. This has implications for the study of the New Testament and early Christianity. With insights from cognitive science, we can better understand how people in the ancient Mediterranean world remembered sayings and stories, what they experienced when participating in rituals, how they thought about magic and miracle, and how they felt and reasoned about moral questions. The first three chapters of the book introduce the contemporary study of religion in the framework of evolution, culture, and cognition. In subsequent chapters, the study of the New Testament and early Christianity is reconsidered in light of the cognitive approach, including the formation of gospel traditions, the origins and function of rituals and sacraments, religious experience, ethics and moral norms, as well as the expansion of the Christian movement. In addition to rethinking old questions from a novel perspective, the book also shows how new research questions emerge from the cognitive approach, such as the connection between magic and miracle, the neurological correlates of visionary experiences, and the interaction between social network dynamics and theological development.Less
This monograph makes a case for a cognitive turn in New Testament Studies, both surveying relevant developments in the Cognitive Science of Religion and digging into the field of cognitive and behavioral sciences in search of opportunities of gaining new insights about biblical materials. Over the last few decades, our knowledge of how the human mind and brain work increased dramatically. We can now understand religious traditions, rituals, and visionary experiences in novel ways. This has implications for the study of the New Testament and early Christianity. With insights from cognitive science, we can better understand how people in the ancient Mediterranean world remembered sayings and stories, what they experienced when participating in rituals, how they thought about magic and miracle, and how they felt and reasoned about moral questions. The first three chapters of the book introduce the contemporary study of religion in the framework of evolution, culture, and cognition. In subsequent chapters, the study of the New Testament and early Christianity is reconsidered in light of the cognitive approach, including the formation of gospel traditions, the origins and function of rituals and sacraments, religious experience, ethics and moral norms, as well as the expansion of the Christian movement. In addition to rethinking old questions from a novel perspective, the book also shows how new research questions emerge from the cognitive approach, such as the connection between magic and miracle, the neurological correlates of visionary experiences, and the interaction between social network dynamics and theological development.
Alvaro Pascual-Leone and Adolfo Plasencia
- Published in print:
- 2017
- Published Online:
- January 2018
- ISBN:
- 9780262036016
- eISBN:
- 9780262339308
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262036016.003.0024
- Subject:
- Society and Culture, Technology and Society
In this dialogue, the Harvard neuroscientist, Alvaro Pascual-Leone initially reflects on the importance of ‘unlearning’ and forgetting. He then gives a detailed explanation of, and how he carries ...
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In this dialogue, the Harvard neuroscientist, Alvaro Pascual-Leone initially reflects on the importance of ‘unlearning’ and forgetting. He then gives a detailed explanation of, and how he carries out, transcraneal magnetic stimulation (TMS) and how he uses this technology to fight diseases, as well as explaining his experiments on inattentional blindness. He then discusses how the brain acts as a hypothesis generator and whether the brain, the mind and the soul are different things or not. Later reflect on the questions: Is the mind and what we are a consequence of the brain’s structure? Do changes in the brain change our reality? And why are a person’s dreams important? Then he explains how freewill and decision-making work from the brain, and relates his vision of intelligence and where it may be generated from, explaining the differences between the mind and the brain. He finally reflects on what is known so far about the brain’s “dark energy” and the way we are continuously being surprised by the wonders of the brain's plasticity.Less
In this dialogue, the Harvard neuroscientist, Alvaro Pascual-Leone initially reflects on the importance of ‘unlearning’ and forgetting. He then gives a detailed explanation of, and how he carries out, transcraneal magnetic stimulation (TMS) and how he uses this technology to fight diseases, as well as explaining his experiments on inattentional blindness. He then discusses how the brain acts as a hypothesis generator and whether the brain, the mind and the soul are different things or not. Later reflect on the questions: Is the mind and what we are a consequence of the brain’s structure? Do changes in the brain change our reality? And why are a person’s dreams important? Then he explains how freewill and decision-making work from the brain, and relates his vision of intelligence and where it may be generated from, explaining the differences between the mind and the brain. He finally reflects on what is known so far about the brain’s “dark energy” and the way we are continuously being surprised by the wonders of the brain's plasticity.
