Methods for Network Analysis Book Club
Welcome
Book club meetings
Pace
1
(skip)
2
(skip)
3
(skip)
4
R Basics
4.1
Intro to the book club
4.1.1
What is this book about?
4.1.2
Who is the author?
4.1.3
What makes a “network”?
4.2
Vectors, matrices and data.frames
4.3
Indexing and Subsetting
4.4
Loading Packages
4.5
Meeting Videos
4.5.1
Cohort 1
5
Understanding Network Data Structures
5.1
Edge lists
5.2
Adjacency matrices (recommended structure)
5.3
Meeting Videos
5.3.1
Cohort 1
6
Your First Network
6.1
Creating a project
6.2
Loading data into R
6.3
Manual data entry
6.4
From data to networks
6.5
Meeting Videos
6.5.1
Cohort 1
7
Network Visualization and Aesthetics
7.1
The Basics
7.1.1
Nodes
7.2
Edges
7.3
Layouts
7.4
Adding attributes to a network object
7.5
Plotting based on attributes
7.5.1
Cohort 1
8
Ego Networks
8.1
8.2
Meeting Videos
8.2.1
Cohort 1
9
Calculating Network Size and Density
9.1
Load data
9.2
Number of vertices
9.3
Number of edges
9.4
Density
9.5
Meeting Videos
9.5.1
Cohort 1
10
Affiliation Data
10.1
Indirect connections
10.1.1
Unipartite Projection
10.2
Tripartite network analysis?
10.2.1
Lab
10.3
Meeting Videos
10.3.1
Cohort 1
11
Transitivity, Structural Balance, and Hierarchy
11.1
Load the data
11.2
The Dyad
11.3
The Triad
11.4
Calculating a triad census
11.5
Random graphs galore
11.6
Producing a tau statistic
11.7
Meeting Videos
11.7.1
Cohort 1
12
Centrality
12.1
SLIDE 1
12.2
Meeting Videos
12.2.1
Cohort 1
13
Bridges, Holes, the Small World Problem, and Simulation
13.1
It’s a small world after all
13.2
Measuring connectivity of networks
13.3
One last thing
13.4
Meeting Videos
13.4.1
Cohort 1
14
Finding Groups in Networks
14.1
SLIDE 1
14.2
Meeting Videos
14.2.1
Cohort 1
15
Homophily and Exponential Random Graphs (ERGM)
15.1
SLIDE 1
15.2
Meeting Videos
15.2.1
Cohort 1
16
Positional Analysis in Networks
16.1
SLIDE 1
16.2
Meeting Videos
16.2.1
Cohort 1
17
Culture and Networks
17.1
SLIDE 1
17.2
Meeting Videos
17.2.1
Cohort 1
18
Dynamics
18.1
SLIDE 1
18.2
Meeting Videos
18.2.1
Cohort 1
Published with bookdown
Methods for Network Analysis Book Club
Chapter 5
Understanding Network Data Structures
Learning objectives:
Generating networks from edge lists or adjacency matrices.