Book contents
- Network Analysis
- Structural Analysis in the Social Sciences
- Network Analysis
- Copyright page
- Contents
- Figures
- Tables
- Acknowledgments
- 1 Introduction
- Part I Thinking Structurally
- 2 What Is Social Structure?
- 3 What Is a Social Network?
- 4 How Are Social Network Data Collected?
- 5 How Are Social Network Data Visualized?
- Part II Seeing Structure
- Part III Making Structural Predictions
- References
- Index
- References
3 - What Is a Social Network?
from Part I - Thinking Structurally
Published online by Cambridge University Press: 21 September 2023
Book contents
- Network Analysis
- Structural Analysis in the Social Sciences
- Network Analysis
- Copyright page
- Contents
- Figures
- Tables
- Acknowledgments
- 1 Introduction
- Part I Thinking Structurally
- 2 What Is Social Structure?
- 3 What Is a Social Network?
- 4 How Are Social Network Data Collected?
- 5 How Are Social Network Data Visualized?
- Part II Seeing Structure
- Part III Making Structural Predictions
- References
- Index
- References
Summary
We outline the core concepts of network analysis, issues of research design, and data collection for different structural questions.
- Type
- Chapter
- Information
- Network AnalysisIntegrating Social Network Theory, Method, and Application with R, pp. 45 - 66Publisher: Cambridge University PressPrint publication year: 2023
References
Suggested Further Reading
Gibbons, Alan. 1985. Algorithmic Graph Theory. New York: Cambridge University Press. (A classic exposition of primary algorithmic approaches to manipulating, searching, and performing search operations on network objects. While some of the routines have been superseded by newer algorithms, this publication provides basics to get anyone started in this line of work.)Google Scholar
Harary, Frank. 1969. Graph Theory. Reading, MA: Addison Wesley. (The classic work in the basics of graph theory.)CrossRefGoogle Scholar
Kivelä, Mikko, Arenas, Alex, Barthelemy, Marc et al. 2014. “Multilayer Networks.” Journal of Complex Networks 2: 203–71. (Multilayer networks are one of the most general ways to bind multiple types of nodes and relations in a single analysis object; the approach has proven useful for both cross-context studies and unique approaches to dynamic modeling of networks.)CrossRefGoogle Scholar
Richards, William, and Seary, Andrew. 2000. “Eigen Analysis of Networks.” Journal of Social Structure 1(2): 1–17. (Eigen structures are key to many network metrics, although their use and mathematical foundations are often understudied in social sciences. This work provides a gentle introduction to what they are and why they matter.)Google Scholar