This course deals with computer science (CS) aspects of social network analysis (SNA), and is open to all students in the master computer science programme at Leiden University.

If you want to participate and are in a different programme, then you should contact the lecturer in advance.


COVID-19 policy. The 2021 SNACS course is an on-site course unless COVID-19 measures in the Netherlands prevent it from being so. The course can not be taken online-only, except if a registered student's country of origin has explicit regulations that prevent the student from being present in the Netherlands.


Course information

Lectures: Fridays from 11:15 to 13:00 in Gorlaeus "Havingazaal" (except Sep 17 & Dec 10: Van Steenis F104)
Lab sessions: Fridays from 9:15 to 11:00 in Snellius rooms 302/304 and 306/308
Prerequisites: a CS bachelor with courses on Algorithms, Data Structures and Data Mining
Literature: provided papers and book chapters (free and digitally available)
Examination: based on presentation, paper, programming, peer review and participation (no exam)
Brightspace link: 2122-S1 Social Network Analysis for Computer Scientists
Study points: 6 ECTS

Need help? Ask your questions during the lab sessions. If it is more urgent, walk by the lecturer or assistant's office. If they are not around, contact snacs@liacs.leidenuniv.nl.

Lecturer: dr. Frank Takes (f.w.takes@liacs.leidenuniv.nl, room 157b)
Assistants: Hanjo Boekhout MSc (h.d.boekhout@liacs.leidenuniv.nl, room 126), Yali Wang MSc (y.wang@liacs.leidenuniv.nl, room 142) and Bart de Zoete BSc (b.de.zoete@umail.leidenuniv.nl)



[Network visualization image]

Network with 1458 nodes and 1948 edges.

Course schedule

  Date Lecture (11:15-13:00) Lab session (9:15-11:00)
1. Sep 10, 2021 Lecture 0: Course information
Lecture 1: Introduction
No lab session in the first week, but if you have not already, please
ensure your Linux account works in room 302/304 and 306/308.
2. Sep 17, 2021 ... ...
3. Sep 24, 2021 ... ...
4. Oct 1, 2021 ... ...
Oct 4, 2020 Deadline for Assignment 1
5. Oct 8, 2021 ... ...
6. Oct 15, 2021 ... ...
7. Oct 22, 2021 ... ...
Oct 29, 2020 Deadline for Assignment 2
8. Oct 29, 2021 ... ...
9. Nov 5, 2021 ... ...
10. Nov 12, 2021 ... ...
11. Nov 19, 2021 ... ...
12. Nov 26, 2021 ... ...
13. Dec 3, 2021 ... ...
14. Dec 10, 2021 ... ...
Dec 13, 2020 Deadline for final course project paper
Dec 20, 2020 Retake deadline for assignments
Dec 23, 2020 Course end. Grades are sent to student administration

Course description

See the e-Studyguide for a more general description.

Topics include: SNA from a CS perspective (graph representation, complexity issues, examples), Graph Structure (power law, small world phenomenon, clustering coefficient, hierarchies), Paths and Distances (neighborhoods, radius, diameter), Spidering and Sampling (BFS, forest fire, random walks), Graph Compression (graph grammars, bitwise tricks, encryption, hashing), Centrality (degree centrality, closeness centrality, betweenness centrality, rating and ranking), Centrality and Webgraphs (HITS, PageRank, structure of the web), Community Detection (spectral clustering, modularity), Visualization (force-based algorithms, Gephi, NodeXL), Graph Models (random graphs, preferential attachment), Link Prediction (structure, semantics, prediction algorithms, graph mining), Contagion (diffusion of information, spreading activation, gossipping) and Privacy and Anonymity ((de-)anonymizing graphs, ethical aspects, privacy issues) and various other topics that have been added over the years but are not yet in the list above.

The course was also given in 2014, 2015, 2016, 2017, 2018, 2019 and 2020.