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Analyzing Social Networks

Analyzing Social Networks

Second Edition
Additional resources:

February 2018 | 384 pages | SAGE Publications Ltd

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 Second 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 text is the perfect student-friendly introduction to social network analysis. 

Chapter 1: Introduction
Why networks?

What are networks?

Types of relations

Goals of analysis

Network variables as explanatory variables

Network variables as outcome variables

Chapter 2: Mathematical Foundations

Paths and components

Adjacency matrices

Ways and modes

Matrix products

Chapter 3: Research Design
Experiments and field studies

Whole-network and personal-network research designs

Sources of network data

Types of nodes and types of ties

Actor attributes

Sampling and bounding

Sources of data reliability and validity issues

Ethical considerations

Chapter 4: Data Collection
Network questions

Question formats

Interviewee burden

Data collection and reliability

Archival data collection

Data from electronic sources

Chapter 5: Data Management
Data import

Cleaning network data

Data transformation


Cognitive social structure data

Matching attributes and networks

Converting attributes to matrices

Data export

Chapter 6: Multivariate Techniques Used in Network Analysis
Multidimensional scaling

Correspondence analysis

Hierarchical clustering

Chapter 7: Visualization

Embedding node attributes

Node filtering

Ego networks

Embedding tie characteristics

Visualizing network change

Exporting visualizations

Closing comments

Chapter 8: Testing Hypotheses
Permutation tests

Dyadic hypotheses

Mixed dyadic–monadic hypotheses

Node level hypotheses

Whole-network hypotheses

Exponential random graph models

Stochastic actor-oriented models (SAOMs)

Chapter 9: Characterizing Whole Networks


Transitivity and the clustering coefficient

Triad census

Centralization and core–periphery indices

Chapter 10: Centrality
Basic concept

Undirected, non-valued networks

Directed, non-valued networks

Valued networks

Negative tie networks

Chapter 11: Subgroups

Girvan–Newman algorithm

Factions and modularity optimization

Directed and valued data

Computational considerations

Performing a cohesive subgraph analysis

Supplementary material

Chapter 12: Equivalence
Structural equivalence

Profile similarity


The direct method

Regular equivalence

The REGE algorithm

Core–periphery models

Chapter 13: Analyzing Two-mode Data
Converting to one-mode data

Converting valued two-mode matrices to one-mode

Bipartite networks

Cohesive subgroups and community detection

Core–periphery models


Chapter 14: Large Networks
Reducing the size of the problem

Choosing appropriate methods


Small-world and scale-free networks

Chapter 15: Ego Networks
Personal-network data collection

Analyzing ego network data

Example 1 of an ego network study

Example 2 of an ego network study


Probably the best method-focused book on social network analysis I have ever read. Clear structure, precise language, great examples. Can not recommend this enough for researchers and students who are interested in learning about social network analysis.
I would not recommend it for bachelor level students as it seems too in-depth to be pure introductory material.

Mr Steffen Triebel
Institut of Management and Or, University of Hannover
June 3, 2019

It gives you just the right amount of info
Good book to have around if you are interested in social network analysis

Miss burcu gumus
Communication Sciences, Dogus University
September 24, 2019

a very useful read/text

Mr Phillip Morgan
Faculty of Education and Training, University of Wales, Trinity St David
February 26, 2018
Key features
  • Written by the creators of the software discussed in the book.
  • Walks students through from basic concepts to complex applications.
  • Fully updated digital resources including examples, walkthroughs, and exercises.

Sample Materials & Chapters


For instructors

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