Analyzing Social Networks Using R
SAGE Publications Ltd (Verlag)
978-1-5297-2247-5 (ISBN)
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
Stephen Borgatti is the Gatton Endowed Chair of Management at the Gatton College of Business and Economics at the University of Kentucky. He has published extensively in management journals, as well cross-disciplinary journals such as Science and Social Networks. He has published over 100 peer-reviewed articles on network analysis, garnering more than 70,000 Google Scholar citations. With Martin Everett, Steve is co-author of UCINET, a well-known software package for social network analysis, as well as founder of the annual LINKS Center workshop on social network analysis. He is also a 2-term past President of INSNA (the professional association for network researchers) and winner of their Simmel Award for lifetime achievement. Martin Everett is Professor of Social Network Analysis and co-director of the Mitchell Centre for SNA at the University of Manchester. He has published extensively on social network analysis and has over 100 peer-reviewed articles and consulted with government agencies as well as public and private companies. With Stephen Borgatti, Martin is co-author of UCINET, a well-known software package for social network analysis and is co-editor of the journal Social Networks. He is also a past President of INSNA (the professional association for network researchers) and winner of their Simmel Award for lifetime achievement. He was elected as an academician to the UK Academy of Social Sciences in 2004. Jeffrey Johnson is a University Term Professor of Anthropology at the University of Florida. He was a former Program Manager with the Army Research Office (IPA) where he started the basic science research program in the social sciences. He has conducted extensive long-term research, supported by the National Science Foundation, comparing group dynamics and the evolution of social networks of over-wintering crews at the American South Pole Station, with those at the Polish, Russian, Chinese, and Indian Antarctic Stations. In related research, he has studied aspects of team cognition and social networks on success in simulated space missions. He has published extensively in anthropological, sociological, biological, aerospace, and marine science journals and was the founding editor of the Journal of Quantitative Anthropology, co-editor of the journal Human Organization, and the author of Selecting Ethnographic Informants, Sage, 1990. Filip Agneessens is an Associate Professor at the Department of Sociology and Social Research, University of Trento. He has published on a diversity of topics related to social networks, including measures of centrality, statistical models, ego-networks and social support, two-mode networks, negative ties, multilevel networks and issues related to data collection. He has also applied social network analysis to understand the antecedents and consequences of interactions among employees, and in particular within teams. Together with Martin Everett, he was a guest-editor for a special issue on “Advances in Two-mode Social Network Analysis” in the journal Social Networks, and together with Nick Harrigan and Joe Labianca he guest-edited a special issue on “Negative and Signed Tie Networks”. He has taught numerous introductory and advanced social network courses and workshops over the last 15 years.
Chapter 1: Introduction
Chapter 2: Mathematical Foundations
Chapter 3: Research Design
Chapter 4: Data Collection
Chapter 5: Data Management
Chapter 6: Multivariate Techniques Used in Network Analysis
Chapter 7: Visualization
Chapter 8: Local Node-Level Measures
Chapter 9: Centrality
Chapter 10: Group-level measures
Chapter 11: Subgroups and community detection
Chapter 12: Equivalence
Chapter 13: Analyzing Two-mode Data
Chapter 14: Introduction to Inferential Statistics for Complete Networks
Chapter 15: ERGMs and SAOMs
| Erscheinungsdatum | 04.05.2022 |
|---|---|
| Verlagsort | London |
| Sprache | englisch |
| Maße | 170 x 242 mm |
| Gewicht | 660 g |
| Themenwelt | Sozialwissenschaften ► Soziologie ► Empirische Sozialforschung |
| ISBN-10 | 1-5297-2247-0 / 1529722470 |
| ISBN-13 | 978-1-5297-2247-5 / 9781529722475 |
| Zustand | Neuware |
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