Social Network Analysis: Methods and Examples 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.

Inferential Methods in Social Network Analysis
Learning Objectives
  • Explain how permutation is used for inferential statistics in social network analysis
  • Discuss the underlying process of QAP correlation when examining the relations between two matrices/graphs
  • Demonstrate the QAP regression when using UCINET to predict one outcome matrix with multiple explanatory matrices
  • Examine the theoretical assumptions, the history, and development for ERGM
  • Explain the three aspects that ERGM looks at when explaining network ties in a full network
  • Construct the ERGM statistical modeling when using ERGM to investigate a given network with the three exogenous aspects
  • Interpret the coefficients, standard errors, and model statistics in ERGM outputs generated by SIENA 3.0

The previous chapter discussed descriptive methods in social network analysis. But often we would like to know whether a feature in the ...

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