The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
Alyssa Fahringer - One of the best experts on this subject based on the ideXlab platform.
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InfoGuides: Network Analysis: Network Analysis
2020Co-Authors: Alyssa FahringerAbstract:This guide defines Network Analysis and discusses several Network Analysis tools and methods
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InfoGuides: Network Analysis: Network Analysis Tools
2020Co-Authors: Alyssa FahringerAbstract:This guide defines Network Analysis and discusses several Network Analysis tools and methods
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InfoGuides: Network Analysis: Get Help
2020Co-Authors: Alyssa FahringerAbstract:This guide defines Network Analysis and discusses several Network Analysis tools and methods
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InfoGuides: Network Analysis: Further Resources
2020Co-Authors: Alyssa FahringerAbstract:This guide defines Network Analysis and discusses several Network Analysis tools and methods
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InfoGuides: Network Analysis: Citation Analysis
2020Co-Authors: Alyssa FahringerAbstract:This guide defines Network Analysis and discusses several Network Analysis tools and methods
Noa Pinter-wollman - One of the best experts on this subject based on the ideXlab platform.
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The use of multilayer Network Analysis in animal behaviour
Animal Behaviour, 2019Co-Authors: Kelly R. Finn, Mason A Porter, Matthew J Silk, Noa Pinter-wollmanAbstract:Network Analysis has driven key developments in research on animal behaviour by providing quantitative methods to study the social structures of animal groups and populations. A recent formalism, known as multilayer Network Analysis, has advanced the study of multifaceted Networked systems in many disciplines. It offers novel ways to study and quantify animal behaviour through connected ‘layers’ of interactions. In this article, we review common questions in animal behaviour that can be studied using a multilayer approach, and we link these questions to specific analyses. We outline the types of behavioural data and questions that may be suitable to study using multilayer Network Analysis. We detail several multilayer methods, which can provide new insights into questions about animal sociality at individual, group, population and evolutionary levels of organization. We give examples for how to implement multilayer methods to demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. Finally, we discuss caveats to undertaking multilayer Network Analysis in the study of animal social Networks, and we call attention to methodological challenges for the application of these approaches. Our aim is to instigate the study of new questions about animal sociality using the new toolbox of multilayer Network Analysis.
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The use of multilayer Network Analysis in animal behaviour
arXiv: Populations and Evolution, 2017Co-Authors: Kelly R. Finn, Mason A Porter, Matthew J Silk, Noa Pinter-wollmanAbstract:Network Analysis has driven key developments in research on animal behaviour by providing quantitative methods to study the social structures of animal groups and populations. A recent formalism, known as \emph{multilayer Network Analysis}, has advanced the study of multifaceted Networked systems in many disciplines. It offers novel ways to study and quantify animal behaviour as connected 'layers' of interactions. In this article, we review common questions in animal behaviour that can be studied using a multilayer approach, and we link these questions to specific analyses. We outline the types of behavioural data and questions that may be suitable to study using multilayer Network Analysis. We detail several multilayer methods, which can provide new insights into questions about animal sociality at individual, group, population, and evolutionary levels of organisation. We give examples for how to implement multilayer methods to demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. Finally, we discuss caveats to undertaking multilayer Network Analysis in the study of animal social Networks, and we call attention to methodological challenges for the application of these approaches. Our aim is to instigate the study of new questions about animal sociality using the new toolbox of multilayer Network Analysis.
Michel Buffa - One of the best experts on this subject based on the ideXlab platform.
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Semantic Social Network Analysis
2009Co-Authors: Guillaume Erétéo, Fabien Gandon, Olivier Corby, Michel BuffaAbstract:Social Network Analysis (SNA) has been widely studied since the middle of the 20th century. Research in this field tries to understand and exploit the key features of social Networks in order to manage their life cycle and predict their evolutions. Detecting strategic positions, roles and communities are among its main concerns. The increasingly popular web 2.0 sites form the largest social Network. Some researchers apply classical methods from social Network Analysis (SNA) to such online Networks; others provide models to leverage the semantics of their representation. In this paper, we propose to leverage semantic web technologies to merge and exploit the best features of each of these approaches. Furthermore, we show how to facilitate and enhance the Analysis of online social Networks, exploiting the power of semantic social Network Analysis.
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Semantic Social Network Analysis
Proceedings of the Web Science, WebSci 2009, 2001Co-Authors: Guillaume Erétéo, Fabien Gandon, Olivier Corby, Sophia Antipolis, Michel BuffaAbstract:Social Network Analysis (SNA) tries to understand and exploit the key features of social Networks in order to manage their life cycle and predict their evolution. Increasingly popular web 2.0 sites are forming huge social Network. Classical methods from social Network Analysis (SNA) have been applied to such online Networks. In this paper, we propose leveraging semantic web technologies to merge and exploit the best features of each domain. We present how to facilitate and enhance the Analysis of online social Networks, exploiting the power of semantic social Network Analysis.
John Scott - One of the best experts on this subject based on the ideXlab platform.
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social Network Analysis a handbook
2000Co-Authors: John ScottAbstract:Networks and Relations The Development of Social Network Analysis Handling Relational Data Lines, Direction and Density Centrality and Centralization Components, Cores, and Cliques Positions, Roles, and Clusters Dimensions and Displays Appendix Social Network Packages
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social Network Analysis
2000Co-Authors: John ScottAbstract:This paper reports on the development of social Network Analysis, tracing its origins in classical sociology and its more recent formulation in social scientific and mathematical work. It is argued that the concept of social Network provides a powerful model for social structure, and that a number of important formal methods of social Network Analysis can be discerned. Social Network Analysis has been used in studies of kinship structure, social mobility, science citations, contacts among members of deviant groups, corporate power, international trade exploitation, class structure, and many other areas. A review of the formal models proposed in graph theory, multidimensional scaling, and algebraic topology is followed by extended illustrations of social Network Analysis in the study of community structure and interlocking directorships.
Kelly R. Finn - One of the best experts on this subject based on the ideXlab platform.
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The use of multilayer Network Analysis in animal behaviour
Animal Behaviour, 2019Co-Authors: Kelly R. Finn, Mason A Porter, Matthew J Silk, Noa Pinter-wollmanAbstract:Network Analysis has driven key developments in research on animal behaviour by providing quantitative methods to study the social structures of animal groups and populations. A recent formalism, known as multilayer Network Analysis, has advanced the study of multifaceted Networked systems in many disciplines. It offers novel ways to study and quantify animal behaviour through connected ‘layers’ of interactions. In this article, we review common questions in animal behaviour that can be studied using a multilayer approach, and we link these questions to specific analyses. We outline the types of behavioural data and questions that may be suitable to study using multilayer Network Analysis. We detail several multilayer methods, which can provide new insights into questions about animal sociality at individual, group, population and evolutionary levels of organization. We give examples for how to implement multilayer methods to demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. Finally, we discuss caveats to undertaking multilayer Network Analysis in the study of animal social Networks, and we call attention to methodological challenges for the application of these approaches. Our aim is to instigate the study of new questions about animal sociality using the new toolbox of multilayer Network Analysis.
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The use of multilayer Network Analysis in animal behaviour
arXiv: Populations and Evolution, 2017Co-Authors: Kelly R. Finn, Mason A Porter, Matthew J Silk, Noa Pinter-wollmanAbstract:Network Analysis has driven key developments in research on animal behaviour by providing quantitative methods to study the social structures of animal groups and populations. A recent formalism, known as \emph{multilayer Network Analysis}, has advanced the study of multifaceted Networked systems in many disciplines. It offers novel ways to study and quantify animal behaviour as connected 'layers' of interactions. In this article, we review common questions in animal behaviour that can be studied using a multilayer approach, and we link these questions to specific analyses. We outline the types of behavioural data and questions that may be suitable to study using multilayer Network Analysis. We detail several multilayer methods, which can provide new insights into questions about animal sociality at individual, group, population, and evolutionary levels of organisation. We give examples for how to implement multilayer methods to demonstrate how taking a multilayer approach can alter inferences about social structure and the positions of individuals within such a structure. Finally, we discuss caveats to undertaking multilayer Network Analysis in the study of animal social Networks, and we call attention to methodological challenges for the application of these approaches. Our aim is to instigate the study of new questions about animal sociality using the new toolbox of multilayer Network Analysis.
