Social & Economic Networks (a short introduction)

Jaromir Kovarik (University of the Basque Country, University of West Bohemia, and CERGE-EI)

Email: jaromir.kovarik@ehu.eus.

This webpage contains all the material for a two- or three-day course "Social and Economic Network," taught since 2019 in the Master in Data Science and Organizational Behavior in the Burgundy School of Business (BSB), Dijon, France.

SLIDES

1. Preliminary Examples

2. Background on Networks

3. Visualization and Analysis of Networks using R

4. A Few Network Cases

ADDITIONAL MATERIAL

Statistical package R manual: An introduction to R in pdf format.

Igraph package. Manual to the igraph package for R (or see the online manual). This package is designed for performing network analysis.

To install igraph, you can simply type install.packages("igraph") in R.

DATA;

The data and code used in the examples in the empirical part of the paper (see the slides for "4. Visualization and Analysis of Networks using R"):

(1) Nodes (nodes.csv)

(2) Links (links.csv)

(3) Node information (data.csv)

You can also download here one network plotted in class and the R code from class.

HOMEWORK ASSIGNMENT:

All students are obliged to hand in an assignment, which will be graded. The grade from this mini-course will form part of the final grade from the module "Behavioral Strategies for Business." The homework should be handed in to me via email.

The assignment has to be done individually by each student.

Deadline: April 24, 2024.

For the task, find data on a real-life social network. It can be any network of your choice. You can for example find a lot of network data on the Stanford Large Network Dataset Collection or Network Repository, but many other sources of data exist online. Just be creative! Your task is the following:

(a) Read the network into R

(b) Describe what the network represents and visualize it clearly. If the network is too large, visualize one part.