Master in Computational Social Science
DURATION
1 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
Request application deadline
EARLIEST START DATE
Sep 2025
TUITION FEES
EUR 9,900 *
STUDY FORMAT
On-Campus
* current fees for the 23/24 academic year
Introduction
Digital technology has revolutionized society and the way we study it. Much of human interaction is recorded in the form of a digital footprint, and analyzing it allows us to gain an unprecedented understanding of society and how it works. In this new context, the figure of the computational social scientist emerges. This new profile combines the characteristics of the social scientist with new computational approaches based on predictive modeling, text analysis and network science to analyze society in a new and revealing way.
The Master in Computational Social Science offers specialized training in cutting-edge computational and quantitative analysis techniques oriented to the study of the Social Sciences. This program prepares you to take advantage of complex data and advanced computational tools to understand society and human behavior.
The Master is preferably geared towards students with a background in Social Sciences, Economics, Communication and Law, and prepares them to work in the professional and academic fields and to lead and supervise interdisciplinary teams in the field of Computational Social Sciences.
Master in Numbers
- Maximum 35 students per class
- 90% of professors with Ph.D. degree
- The demand for computational social scientists has grown quickly in recent years and is expected to grow even more in the future.
Admissions
Scholarships and Funding
For the academic year 2024-2025 a call has been published for a maximum of 3 scholarships for payment of the net enrolment fees for students accepted into the Master’s, with the following provision:
- 3 scholarships of €1,500
To apply, you must have completed the application for admission to the Master’s.
Curriculum
Formative Complements *
- Introduction to R programming
- Basic statistics
Year 1 - Semester 1
- Foundations of Computational Social Science
- Behavioral theories in the Social Sciences
- Research design for Social Sciences
- Survey research methodology
- Data programming
- Data visualization
- Statistics and data science I
- Statistics and data science II
Year 1 - Semester 2
- Social and ethical issues of Big Data & AI
- Survey research methodology II
- Social network analysis
- Master's Thesis Seminar
- Data harvesting
- Text mining
- Advanced modelling
- Causal inference for Social Science
Master's Thesis