Designing Empirical Social Networks Research

A user-friendly introductory guide to the empirical study of social networks. Jennifer M. Larson presents the fundamentals of social networks in an intuition-forward way which guides theory-driven research design. Substantial attention is devoted to a framework for developing a network theory that will steer data collection to be maximally informative and minimally frustrating. Other features include: Coverage of a range of practical topics including selecting operationalizations, cutting survey costs, and cleaning data; A tutorial for getting started in analyzing networks in R; Technical sections full of examples, points to hone intuition, and practice problems with solutions. Designing Empirical Social Networks Research will be a valuable tool for advanced undergraduates, Ph.D. students in the social sciences, especially political science, and researchers across the social sciences who are new to the study of networks.

Table des matières

1. Introduction to social networks research; 2. Describing and interpreting social network features; 3. Accounting for substantive network features; 4. Crafting a network theory; 5. Moving from theory to Empirics; 6. Acquiring network data; 7. Preparing network data; 8. Working with network data in R; 9. Conclusion: where to turn next; Selected answers; Glossary; Bibliography; Index.

A propos de l'auteur

Jennifer M. Larson is Associate Professor in the Department of Political Science at Vanderbilt University.

Détails du produit

• Auteurs: Jennifer M Larson, Jennifer M. Larson, Jennifer M. (Vanderbilt University Larson, Larson Jennifer M.
• Edition: Cambridge University Press ELT
• Langues: Anglais
• Format d'édition: Livre Relié
• Sortie: 31.08.2024
• EAN: 9781009484183
• ISBN: 978-1-0-0948418-3
• Pages: 186
• Thème: Methods for Social Inquiry
• Catégories: Sciences naturelles, médecine, informatique, technique > Informatique, ordinateurs > Général, dictionnaires; Sciences sociales, droit, économie > Sciences sociales en général; POLITICAL SCIENCE / History & Theory, SOCIAL SCIENCE / Research, SOCIAL SCIENCE / Statistics, REFERENCE / Research, Political science & theory, Social research & statistics, Political science and theory, Social research and statistics, Data analysis: general, Data science and analysis: general, Research methods: general, Data science and analysis