Analyzing Social Networks Using R
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Analyzing Social Networks Using R
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Author : Stephen P. Borgatti
language : en
Publisher: SAGE
Release Date : 2022-04-21
Analyzing Social Networks Using R written by Stephen P. Borgatti and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-21 with Social Science categories.
This approachable book introduces network research in R, walking you through every step of doing social network analysis. Drawing together research design, data collection and data analysis, it explains the core concepts of network analysis in a non-technical way. The book balances an easy to follow explanation of the theoretical and statistical foundations underpinning network analysis with practical guidance on key steps like data management, preparation and visualisation. With clarity and expert insight, it: • Discusses measures and techniques for analyzing social network data, including digital media • Explains a range of statistical models including QAP and ERGM, giving you the tools to approach different types of networks • Offers digital resources like practice datasets and worked examples that help you get to grips with R software
Analyzing Social Networks
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Author : Stephen P Borgatti
language : en
Publisher: SAGE
Release Date : 2018-01-08
Analyzing Social Networks written by Stephen P Borgatti and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-08 with Social Science categories.
Designed to walk beginners through core aspects of collecting, visualizing, analyzing, and interpreting social network data, this book will get you up-to-speed on the theory and skills you need to conduct social network analysis. Using simple language and equations, the authors provide expert, clear insight into every step of the research process -- including basic maths principles -- without making assumptions about what you know. With a particular focus on NetDraw and UCINET, the book introduces relevant software tools step-by-step in an easy to follow way. In addition to the fundamentals of network analysis and the research process, this new edition focuses on: Digital data and social networks like Twitter Statistical models to use in SNA, like QAP and ERGM The structure and centrality of networks Methods for cohesive subgroups/community detection Supported by new chapter exercises, a glossary, and a fully updated companion website, this edition is the perfect student-friendly introduction to social network analysis.
Introduction To Social Network Analysis With R
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Author : Michal Bojanowski
language : en
Publisher: John Wiley & Sons
Release Date : 2022-04-22
Introduction To Social Network Analysis With R written by Michal Bojanowski and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-22 with categories.
Introduction to Social Network Analysis with R provides an introduction to performing SNA studies using R, combining the theories of social networks and methods of social network analysis with the R environment as an open source system for statistical data analysis and graphics.
Applied Social Network Analysis With R Emerging Research And Opportunities
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Author : Gençer, Mehmet
language : en
Publisher: IGI Global
Release Date : 2020-02-07
Applied Social Network Analysis With R Emerging Research And Opportunities written by Gençer, Mehmet and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-07 with Computers categories.
Understanding the social relations within the fields of business and economics is vital for the promotion of success within a certain organization. Analytics and statistics have taken a prominent role in marketing and management practices as professionals are constantly searching for a competitive advantage. Converging these technological tools with traditional methods of business relations is a trending area of research. Applied Social Network Analysis With R: Emerging Research and Opportunities is an essential reference source that materializes and analyzes the issue of structure in terms of its effects on human societies and the state of the individuals in these communities. Even though the theme of the book is business-oriented, an approach underlining and strengthening the ties of this field of study with social sciences for further development is adopted throughout. Therefore, the knowledge presented is valid for analyzing not only the organization of the business world but also for the organization of any given community. Featuring research on topics such as network visualization, graph theory, and micro-dynamics, this book is ideally designed for researchers, practitioners, business professionals, managers, programmers, academicians, and students seeking coverage on analyzing social and business networks using modern methods of statistics, programming, and data sets.
A User S Guide To Network Analysis In R
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Author : Douglas Luke
language : en
Publisher: Springer
Release Date : 2015-12-14
A User S Guide To Network Analysis In R written by Douglas Luke and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-14 with Mathematics categories.
Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists. The mathematical foundations of network analysis are emphasized in an accessible way and readers are guided through the basic steps of network studies: network conceptualization, data collection and management, network description, visualization, and building and testing statistical models of networks. As with all of the books in the Use R! series, each chapter contains extensive R code and detailed visualizations of datasets. Appendices will describe the R network packages and the datasets used in the book. An R package developed specifically for the book, available to readers on GitHub, contains relevant code and real-world network datasets as well.
Analyzing Social Networks
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Author : Stephen P Borgatti
language : en
Publisher: SAGE Publications Limited
Release Date : 2024-02-22
Analyzing Social Networks written by Stephen P Borgatti and has been published by SAGE Publications Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-22 with Social Science categories.
Kickstart your research with this practical, bestselling guide to doing social network analysis. Get to grips with the mathematical foundations and learn how to use software tools such as NeTDraw and UNICET to reach your research goals. Supporting you step-by-step through the entire research process, from design and data collection to coding, visualisation, and analysis, the book also offers: • Case studies and examples using real data • Exercises drawn from the authors’ decades of teaching experience • Online access to datasets, worked examples and a software manual to help you practice your skills. Whether you are new to social network analysis or an experienced researcher, this approachable book is your technical toolbox and research companion all in one.
Network Analysis And Visualization In R
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Author : Alboukadel Kassambara
language : en
Publisher: STHDA
Release Date : 2017-11-26
Network Analysis And Visualization In R written by Alboukadel Kassambara and has been published by STHDA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-26 with categories.
Social network analysis is used to investigate the inter-relationship between entities. Examples of network structures, include: social media networks, friendship networks and collaboration networks. This book provides a quick start guide to network analysis and visualization in R. You'll learn, how to: - Create static and interactive network graphs using modern R packages. - Change the layout of network graphs. - Detect important or central entities in a network graph. - Detect community (or cluster) in a network.
Statistical Analysis Of Network Data With R
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Author : Eric D. Kolaczyk
language : en
Publisher: Springer
Release Date : 2014-05-22
Statistical Analysis Of Network Data With R written by Eric D. Kolaczyk and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-22 with Computers categories.
Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).
Algebraic Analysis Of Social Networks
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Author : J. Antonio R. Ostoic
language : en
Publisher: John Wiley & Sons
Release Date : 2021-02-01
Algebraic Analysis Of Social Networks written by J. Antonio R. Ostoic and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-01 with Mathematics categories.
Presented in a comprehensive manner, this book provides a comprehensive foundation in algebraic approaches for the analysis of different types of social networks such as multiple, signed, and affiliation networks. The study of such configurations corresponds to the structural analysis within the social sciences, and the methods applied for the analysis are in the areas of abstract algebra, combinatorics, and graph theory. Current research in social networks has moved toward the examination of more realistic but also more complex social relations by which agents or actors are connected in multiple ways. Addressing this trend, this book offers hands-on training of the algebraic procedures presented along with the computer package multiplex, written by the book’s author specifically to perform analyses of multiple social networks. An introductory section on both complex networks and for R will feature, however the subjects themselves correspond to advanced courses on social network analysis with the specialization on algebraic models and methods.
Models And Methods In Social Network Analysis
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Author : Peter J. Carrington
language : en
Publisher: Cambridge University Press
Release Date : 2005-02-07
Models And Methods In Social Network Analysis written by Peter J. Carrington and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-02-07 with Social Science categories.
Models and Methods in Social Network Analysis, first published in 2005, presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Faust's Social Network Analysis: Methods and Applications, it is a collection of articles by leading methodologists reviewing advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodelling, the analysis of diffusion through networks, the analysis of affiliation or 'two-mode' networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphical techniques for exploring network data, and software for the analysis of social networks.