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Social Network Analysis: Methods and Examples by Song Yang, Franziska B. Keller, and Lu Zheng prepares social science students to conduct their own social network analysis (SNA) by covering basic methodological tools along with illustrative examples from various fields. This innovative book takes a conceptual rather than a mathematical approach as it discusses the connection between what SNA methods have to offer and how those methods are used in research design, data collection, and analysis. Four substantive applications chapters provide examples from politics, work and organizations, mental and physical health, and crime and terrorism studies.

Song Yang (Ph.D. University of Minnesota, 2002) is Professor at the Department of Sociology and Criminal Justice at the University of Arkansas. He also holds Qianren Professorship with School of Sociology and Political Science at Shanghai University. His research areas are social network analysis, sociology of work, and organizational studies. He published Social Network Analysis, Second Edition with David Knoke (Sage, 2008), and the Invisible Hands of Political Parties in Presidential Elections: Party Activists and Political Aggregation from 2004 to 2012 with Andrew Dowdle, Scott Limbocker, Patrick A. Stewart, and Karen Sebold (Palgrave MacMillan, 2013). He has published more than 20 articles in various peer reviewed journals such as Party Politics, Social Science Research, Sociological Spectrum, and Sociological Inquiry.

Preface
About the Authors
Chapter 1: Basics of Social Network Analysis
1.1 Introduction
1.2 The Social Network and How to Represent It
1.3 Types of Networks
1.4 Network Parts and Levels of Analysis
1.5 Networks as Social Structure and Institution
1.6 Theoretical Assumptions
1.7 Causality in Social Network Studies
1.8 A Brief History of Social Network Analysis
Chapter 2: Data Collection
2.1 Boundary Specification
2.2 Data Collection Process
2.3 Informant Bias and Issue of Reliability
2.4 Archival Data
Chapter 3: Descriptive Methods in Social Network Analysis
3.1 Graph and Matrix–Social Network Representation
3.2 Density
3.3 Centrality, Centralization, and Prestige
3.4 Cliques
3.5 Multidimensional Scaling (MDS) and Dendogram
3.6 Structural Equivalence
3.7 Two-Mode Networks and Bipartite Matrix
Chapter 4: Inferential Methods in Social Network Analysis
4.1 Permutation and QAP (Quadratic Assignment Procedure) Correlation
4.2 P* or Exponential Random Graph Model (ERGM)
Chapter 5: Social Network Analysis of Work and Organizations
5.1 Personal Connections and Labor Market Processes
5.2 Intra-Organizational Networks
5.3 Inter-Organizational Relations
Chapter 6: Social Network Analysis in Crime and Terrorism
6.1 Personal Networks, Delinquency, and Crime
6.2 Neighborhood Networks
6.3 Criminal Networks
6.4 Analyzing Social Networks of Terror
Chapter 7: Social Network Analysis in Emotional and Physical Health
7.1 Social Network Analysis and Emotional Health
7.2 Social Network Analysis in Physical Fitness
7.3 Social Network Analysis and Illicit Drug Use
7.4 Social Network Analysis and Sexually Transmitted Disease
Chapter 8: Political Networks
8.1 American Politics
8.2 Networks in International Relations
Glossary
References
Index
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