Social Network Analysis for Computer Scientists
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 in the 2024 edition and are in a different programme, then you should contact the lecturer in advance.
Course information
Lectures: Fridays from 9:00 to 10:45 in Gorlaeus room BM1.33
Lab sessions: Fridays from 11:00 to 12:45 in Gorlaeus room DM0.09 an DM0.13
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: 2425-S1 Social Network Analysis for Computer Scientists
Study guide link: Social Network Analysis for Computer Scientists
Study points: 6 ECTS
Lecturer: dr. Frank Takes (f.w.takes@liacs.leidenuniv.nl, room BE 3.07)
Assistant Lecturer: dr. Vincent Traag (v.a.traag@cwts.leidenuniv.nl)
Assistants:
Rachel de Jong (head TA; room BE 3.03),
dr. Francesco Bariatti (room BE 3.09),
Hanjo Boekhout
(room BE 3.23), Tiago Cumetti, Jakob Lindscheid and Jan Żuromski
![[Network visualization image]](yeast_eccs.jpg)
Network with 1458 nodes and 1948 edges.
Course schedule
| Date | Lecture (9:00-10:45) | Lab session (11:00-12:45) | ||
| 1. | Fri Sep 6, 2024 |
Lecture 0: Course information Lecture 1: Introduction |
Introduction to Gephi Work on Assignment 1 |
|
| 2. | Fri Sep 13, 2024 | ... | ... | |
Mon Sep 30, 2024 |
Deadline for Assignment 1 (AoE; hand in via Brightspace) |
|||
| ... | ... | ... | ... | |
Mon Oct 28, 2024 |
Deadline for Assignment 2 (AoE; hand in via Brightspace) |
|||
| ... | . .. | ... | ... | |
Dec 15, 2024 |
Deadline for final Course Project paper and accompanying code (AoE; hand in via Brightspace) |
|||
| Dec 17, 2024 | Deadline for retake assignment to replace failed assignment(s) (AoE; hand in via email) | |||
| Dec 20, 2024 | Course end. Grades are sent to student administration. | |||
| Jan 31, 2025 | Course project retake deadline | |||
Reading material
Some students have expressed interest in additional reading material to help freshen up on skills and knowledge required for this course.
- To brush up on your Python programming skills, you could do Lecture 0, 1 and 4 of these Scientific Python Lectures.
- To freshen up your LaTeX skills, you could do for example this tutorial (old link, seems ad-infested; choose any other online source).
- MIT has a nice online course on discrete mathematics. Relevant chapters: 5, 6 and 7.
- The (Dutch) Leiden courses Algoritmiek (Algorithms) and Datastructuren (Data structures) might be also interesting to browse through.
- Basic knowledge of concepts in machine learning and data mining are provided, e.g., at the Wikipedia machine learning page.