Stephen P P Borgatti, Martin G. G. Everett, Jeffrey C. C. Johnson, Filip Agneessens

Analyzing Social Networks (eBook, PDF)

• Format: PDF

Produktbeschreibung

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 UCINET 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.

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Produktdetails

• Verlag: SAGE Publications
• Erscheinungstermin: 22. Februar 2024
• Englisch
• ISBN-13: 9781529616163
• Artikelnr.: 69887778

Autorenporträt

Stephen P. Borgatti, PhD 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 as cross-disciplinary journals such as Science and Social Networks. He has published over 100 peer-reviewed articles on network analysis, garnering more than 80,000 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 two-term past president of INSNA (the professional association for network researchers) and winner of their Simmel Award for lifetime achievement.

Inhaltsangabe

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