Admission requirements
None.
Description
Social networks are dynamic, intricate and often surprising in many aspects. Individuals form friendships, exchange messages, organize into communities, and influence each other’s decisions. All of these and many other features can be represented and studied using mathematical tools. These networks have similarities with biological networks such as the brain, financial networks among banks, transportation networks and various other complex systems we experience everyday around our lives. All of these have some common mathematical features.
This course introduces students to the foundational mathematical techniques used to study social networks, from graph theory to probabilistic models. The course emphasizes real world applications, including information spread on social media, the formation of clusters, and the robustness of social systems.
Students will develop analytic thinking and reasoning by working through real life examples and exercises. Lectures introduce the mathematics of networks, while lab sessions provide hands-on experience with data and models using modern graphical tools in R (for example working out basic plots in the igraph package in R).
Course Objectives
After successful completion of this course, students are able to:
Knowledge
Appreciate mathematics for (the history of) liberal arts and sciences, including its use in everyday activities
Understand the relevance of mathematical modeling in social networks.
Identify key graph-theoretical concepts such as centrality, clustering, and connectivity
Recognize probabilistic concepts underlying random graphs and network processes.
Skills
Apply mathematical reasoning to analyze social networks and their dynamics.
Collaboratively engage with real-world datasets using graph-based tools.
Build confidence in interpreting network models, preparing students for interaction between network science, economics, data science, and digital humanities.
Timetable
Timetables for courses offered at Leiden University College in 2025-2026 will be published on this page of the e-Prospectus.
Mode of instruction
The course involves interactive lectures to discuss mathematical concepts from graph theory, linear algebra, and probability, with social applications. Students are expected to revise theoretical concepts before coming to class. The workgroups will focus on solving some exercises and working on real life examples. There will be a group projects to understand real-life data sets. There will also be lab sessions to practice different graphical tools. Homework assignments are for blending theory with practice.
Assessment Method
Participation. 10%
Group project: 25%
Homework assignments: 25%
Final exam: 40%
Reading list
The required textbook is:
- Barabási, A.-L. (2016). Network Science. Cambridge University Press. https://networksciencebook.com/
Registration
Courses offered at Leiden University College (LUC) are usually only open to LUC students and LUC exchange students. Leiden University students who participate in one of the university’s Honours tracks or programmes may register for one LUC course, if availability permits. Registration is coordinated by the Education Coordinator, course.administration@luc.leidenuniv.nl.
Contact
TBC
Remarks
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