Fundamentals of Online (Social) Network Analysis: Data mining, Analysis Methods, and Epistemological Implications

Course Materials (Presentation, Lecture Notes and Notebooks)

LECTURE 1

Online Social Networks, Elements of Networks, Network Measures, Data Sources

Presentation

Slides as PDF

Slides as A4 Portrait PDF, e.g., for handwritten notes

PRACTICAL 1: Getting and Exploring Data with Minet and Python Pandas

Collect and explore data about discussions on Twitter about tank deliveries from Germany to Ukraine.

(Click to start a Jupyter Lab for the exercises)

LECTURE 2

Epistemological/methodological challenges of network science in computational social science, network science as a way to handle organised complexity, research examples

Presentation

Slides as PDF

PRACTICAL 2: Converting Data to Networks for Analysis with Gephi

Convert the data from Practical 1 into edge lists and import them into Gephi for an exploratory network analysis.

PRACTICAL 3: Visualise Dynamic Networks over Time with Gephi

Visualise the data from Practical 2 as a dynamic network over time with Gephi.

Acknowledgements

Thanks to Dr. Maris Männiste and the University of Tartu for funding the development and hosting this course.

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.