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triple helix --- social network analysis --- east and southeast asia --- internet research
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Fraud and manipulation in prediction markets are systematic results of incentive incompatibility, which, if present, have to be detected and balanced. ""Manipulations in Prediction Markets"" gives a critical insight into manipulations that are most likely to occur in prediction markets. In a general approach the book discusses the issue of incentives in markets and the breakdown of the incentive system. On this basis a new way of detecting irregular trading behaviour is introduced.
Wisdom of Crowds --- Social Network Analysis --- Manipulations --- Incentive Systems --- Prediction Markets
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The repertoire of quantitative analytical techniques in disciplines such as ecology, decision science, and evolutionary biology has grown, in part enabled by the development and increased availability of computational resources. Integration of cutting-edge, quantitative tools into veterinary epidemiology that have been borrowed from such disciplines has offered opportunities to advance the study of disease dynamics in animal populations, to improve and guide decision-making related to disease prevention, control, or eradication. Furthermore, the need to explore new analytical methods for veterinary epidemiology has been driven by the increasing availability and complexity of animal disease data. The objective of this e-book is to contribute to current methods in epidemiology by 1) presenting and discussing novel analytical tools that help advance our understanding of epidemiology; and 2) demonstrating how inferences emerging from the application of novel analytical tools can be incorporated into decision-making related to animal health. The e-book constitutes a collection of articles that explore the applications of a variety of analytical methods such as machine learning, Bayesian risk assessment and an advanced form of social network analysis in the modern epidemiologic study of animal diseases.
Decision Making --- Risk Assessment --- social network analysis --- Spatial Epidemiology --- disease surveillance
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The repertoire of quantitative analytical techniques in disciplines such as ecology, decision science, and evolutionary biology has grown, in part enabled by the development and increased availability of computational resources. Integration of cutting-edge, quantitative tools into veterinary epidemiology that have been borrowed from such disciplines has offered opportunities to advance the study of disease dynamics in animal populations, to improve and guide decision-making related to disease prevention, control, or eradication. Furthermore, the need to explore new analytical methods for veterinary epidemiology has been driven by the increasing availability and complexity of animal disease data. The objective of this e-book is to contribute to current methods in epidemiology by 1) presenting and discussing novel analytical tools that help advance our understanding of epidemiology; and 2) demonstrating how inferences emerging from the application of novel analytical tools can be incorporated into decision-making related to animal health. The e-book constitutes a collection of articles that explore the applications of a variety of analytical methods such as machine learning, Bayesian risk assessment and an advanced form of social network analysis in the modern epidemiologic study of animal diseases.
Decision Making --- Risk Assessment --- social network analysis --- Spatial Epidemiology --- disease surveillance
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The repertoire of quantitative analytical techniques in disciplines such as ecology, decision science, and evolutionary biology has grown, in part enabled by the development and increased availability of computational resources. Integration of cutting-edge, quantitative tools into veterinary epidemiology that have been borrowed from such disciplines has offered opportunities to advance the study of disease dynamics in animal populations, to improve and guide decision-making related to disease prevention, control, or eradication. Furthermore, the need to explore new analytical methods for veterinary epidemiology has been driven by the increasing availability and complexity of animal disease data. The objective of this e-book is to contribute to current methods in epidemiology by 1) presenting and discussing novel analytical tools that help advance our understanding of epidemiology; and 2) demonstrating how inferences emerging from the application of novel analytical tools can be incorporated into decision-making related to animal health. The e-book constitutes a collection of articles that explore the applications of a variety of analytical methods such as machine learning, Bayesian risk assessment and an advanced form of social network analysis in the modern epidemiologic study of animal diseases.
Decision Making --- Risk Assessment --- social network analysis --- Spatial Epidemiology --- disease surveillance
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Computational model --- collaborative systems --- Social applications --- Social network analysis --- computational model --- social applications --- social network analysis --- Information technology --- Information society --- Computer science --- Social aspects --- Sociology --- Information superhighway --- IT (Information technology) --- Technology --- Telematics --- Knowledge management
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In line with the multi-disciplinary nature of network research, this edited volume collects both empirical and conceptual contributions that nurture the debate on network research, specifically dealing with the topics of network performance and agency. The contributions draw on different literatures and epistemic approaches and address different levels of analysis, both from a static and a dynamic point of view. It will be of great interest to academics and students developing research in the field of network studies. It will also be of interest to scholars of operations management, organization studies, strategy, innovation, financial management and business history. Anna Moretti is an Associate Professor in the Department of Management at Ca 'Foscari University of Venice, Italy. Lisa Balzarin is a Research Fellow in the Department of Management at Ca 'Foscari University of Venice, Italy.
Industrial organization. --- Social sciences—Network analysis. --- Management. --- Organization. --- Network Research. --- Administration --- Industrial relations --- Organization --- Industries --- Industrial concentration --- Industrial management --- Industrial sociology --- Social sciences --- Network analysis. --- Network analysis (Social sciences) --- SNA (Social network analysis) --- Social network analysis --- System analysis --- Methodology
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Understanding the link between individual behaviour and population organization and functioning has long been central to ecology and evolutionary biology. Behaviour is a response to intrinsic and extrinsic factors including individual state, ecological factors or social interactions. Within a group, each individual can be seen as part of a network of social interactions varying in strength, type and dynamic. The structure of this network can deeply impact the ecology and evolution of individuals, populations and species. Within a group social interactions can take many forms and may significantly affect an individual’s fitness. These interactions may result in complex systems at the group-level, such as in the case of collective decisions (to migrate, to build nest or to forage). Among them, social transmission of information has been studied mostly in vertebrates: fish, birds and mammals including humans. In insects, social learning has been unambiguously demonstrated in social Hymenoptera but this probably reflects limited research effort and recent evidence show that even non-eusocial insects such as Drosophila, cockroaches and crickets can copy the behaviour of others. Compared to individual learning, which requires a trial and error period every generation, social learning can potentially result in the stable transmission of behaviours across generations, leading to cultural traditions in some species. The study of the processes which may facilitate or prevent this transmission and the analyses of the relationship between social network structure and efficiency of social transmission became these recent years an emerging and promising field of research. The goal of this research topic is to present the genetic and socio-environmental factors affecting social interaction and information or pathogen transmission with the integration of experimental approaches, social network analyses and modelling. Importantly, we aim to understand whether a relationship between social network structures and dynamics can reflect the efficiency of social transmission, i.e. can we use social network analysis to predict the social transmission of information or of pathogen, collective decision-making and ultimately the evolutionary trajectory of a group?
Social behavior in animals. --- Animal societies. --- Insects --- social network analysis --- Social transmission --- Primates --- Social Behaviour --- network dynamics --- Epidemiology --- sociality --- methodology
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Understanding the link between individual behaviour and population organization and functioning has long been central to ecology and evolutionary biology. Behaviour is a response to intrinsic and extrinsic factors including individual state, ecological factors or social interactions. Within a group, each individual can be seen as part of a network of social interactions varying in strength, type and dynamic. The structure of this network can deeply impact the ecology and evolution of individuals, populations and species. Within a group social interactions can take many forms and may significantly affect an individual’s fitness. These interactions may result in complex systems at the group-level, such as in the case of collective decisions (to migrate, to build nest or to forage). Among them, social transmission of information has been studied mostly in vertebrates: fish, birds and mammals including humans. In insects, social learning has been unambiguously demonstrated in social Hymenoptera but this probably reflects limited research effort and recent evidence show that even non-eusocial insects such as Drosophila, cockroaches and crickets can copy the behaviour of others. Compared to individual learning, which requires a trial and error period every generation, social learning can potentially result in the stable transmission of behaviours across generations, leading to cultural traditions in some species. The study of the processes which may facilitate or prevent this transmission and the analyses of the relationship between social network structure and efficiency of social transmission became these recent years an emerging and promising field of research. The goal of this research topic is to present the genetic and socio-environmental factors affecting social interaction and information or pathogen transmission with the integration of experimental approaches, social network analyses and modelling. Importantly, we aim to understand whether a relationship between social network structures and dynamics can reflect the efficiency of social transmission, i.e. can we use social network analysis to predict the social transmission of information or of pathogen, collective decision-making and ultimately the evolutionary trajectory of a group?
Social behavior in animals. --- Animal societies. --- Insects --- social network analysis --- Social transmission --- Primates --- Social Behaviour --- network dynamics --- Epidemiology --- sociality --- methodology
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Understanding the link between individual behaviour and population organization and functioning has long been central to ecology and evolutionary biology. Behaviour is a response to intrinsic and extrinsic factors including individual state, ecological factors or social interactions. Within a group, each individual can be seen as part of a network of social interactions varying in strength, type and dynamic. The structure of this network can deeply impact the ecology and evolution of individuals, populations and species. Within a group social interactions can take many forms and may significantly affect an individual’s fitness. These interactions may result in complex systems at the group-level, such as in the case of collective decisions (to migrate, to build nest or to forage). Among them, social transmission of information has been studied mostly in vertebrates: fish, birds and mammals including humans. In insects, social learning has been unambiguously demonstrated in social Hymenoptera but this probably reflects limited research effort and recent evidence show that even non-eusocial insects such as Drosophila, cockroaches and crickets can copy the behaviour of others. Compared to individual learning, which requires a trial and error period every generation, social learning can potentially result in the stable transmission of behaviours across generations, leading to cultural traditions in some species. The study of the processes which may facilitate or prevent this transmission and the analyses of the relationship between social network structure and efficiency of social transmission became these recent years an emerging and promising field of research. The goal of this research topic is to present the genetic and socio-environmental factors affecting social interaction and information or pathogen transmission with the integration of experimental approaches, social network analyses and modelling. Importantly, we aim to understand whether a relationship between social network structures and dynamics can reflect the efficiency of social transmission, i.e. can we use social network analysis to predict the social transmission of information or of pathogen, collective decision-making and ultimately the evolutionary trajectory of a group?
Social behavior in animals. --- Animal societies. --- Insects --- social network analysis --- Social transmission --- Primates --- Social Behaviour --- network dynamics --- Epidemiology --- sociality --- methodology
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