1
Introduction
1.1
What is a Network?
1.2
What is A
Social
Network?
1.3
The Two Faces of Social Network Analysis
2
Graphs
2.1
Social Network Analysis: From Relationships to Graphs
2.2
The Building Blocks of Graphs: Edges and Nodes
2.3
Symmetric Relations and Undirected Graphs
2.4
Asymmetric Relations and Directed Graphs
2.5
Anti-Symmetric Ties and Tree Graphs
2.6
Order and Size
2.7
Average Degree
2.8
Degree Distributions
2.9
Density
2.10
Ego-Centric Networks
2.11
Weighted Ties as a Measure of Strength
2.12
Di-Graphs
2.13
Collecting Network Data
2.14
Practice Problems
2.14.1
2.14.2
2.14.3
2.14.4
2.14.5
2.14.6
3
Matrices
3.1
From Graph to Matrix
3.2
The Adjacency Matrix
3.3
The Symmetric Adjacency Matrix
3.4
The Asymmetric Adjacency Matrix
3.5
The Weighted Matrix
3.6
The Incidence Matrix
3.7
Matrix Operations
3.7.1
3.7.2
3.7.3
3.8
The Reachability Matrix
3.9
Practice Problems
3.9.1
3.9.2
3.9.3
3.9.4
3.9.5
4
Centrality and Composition
4.1
Quantifying Social Structure
4.2
Degree Centrality
4.3
In-degree/Out-degree centrality
4.4
Betweenness Centrality
4.5
K-Path Centrality
4.6
Eigenvector Centrality
4.7
Network Composition Measurements
4.8
Homophily Measures
4.8.1
Relative and Expected Rates
4.8.2
EI Homophily Index
4.8.3
Blau’s Heterogeneity Index
4.9
Practice Problems
4.9.1
5
Subgraphs
5.1
The Foundations of Network Connectivity
5.1.1
5.2
Cliques
5.2.1
5.3
Group Detection
5.4
Practice Problems
5.4.1
5.4.2
5.4.3
6
Where Do Networks Come From?
7
Social Capital: Network Structure and Social Outcomes
8
Whole Network
9
Diffusion
4.6
Eigenvector Centrality
Page Rank (Burris 2003)
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