Lucerne Master in Computational Social Sciences (LUMACSS)
The four LUMACSS modules combine various disciplines such as economics, political science, sociology, law, history and the computational sciences. The broad-based programme also develops statistical and computational methods and thus builds the key skills for the future job market. Coursework comprises a total of 120 ECTS and includes a final master’s thesis and its defence.
1. Social Sciences
This module (20 ECTS) combines courses from political science, history, sociology, economics and law. Coursework covers topics such as the digital economy, big data, comparative media systems, public opinion and Internet law. This module teaches computational scientists the fundamentals of the social sciences while social scientists learn about the manifold aspects and effects of the digitization of modern societies, economies and polities. Students benefit from small-group interactions with experienced faculty and academic peers beyond the confines of their own discipline.
- Foundations of Political Behaviour and Communication
- Big Data – Challenges and opportunities from a sociological perspective
- Internet Law
- Frontiers of Public Opinion
- Comparative Media Systems
- Digital Economy, Data and Online Journalism
2. Statistics and Quantitative Methods
This module (21 ECTS) comprises courses aimed at building students’ scientific literacy. Coursework teaches how to develop rigorous research designs, how to apply appropriate statistical techniques and to master statistical programming, how to replicate real scientific papers and how to find, describe, analyze and visualize social science data. The philosophy driving this module is that “hands-on” applications are part of the learning process.
- Quantitative Research Design I & II
- Replication of Published Scientific Studies
- Introduction to R
- Data Access, Management and Visualization in R
- Statistical Programming
3. Computational Sciences and Digital Skills
This module (22 ECTS) develops multiple key skill sets: data literacy and management skills for dealing with increasingly complex data systems, including data access, handling and storage; computational skills for navigating the Big Data world, including Cloud Computing, Text Analytics, Python programming, Data visualization, Network Analysis, Social Media APIs. This module provides first-class expertise and training to meet the challenges of the datafication era and to seize its opportunities.
- Data Management and computation science skills
- Network analysis with big data
- Python programming
- Data Visualization
- Scraping and Data Mining
This module is supported by swissuniversities and offered in association with the European University Institute in Florence. In the field of computational social sciences we are also actively connected to our international research collaborator, the Berkman Klein Center for Internet & Society at Harvard University.
4. Practical Skills
This module (17 ECTS) offers students three pathways towards acquiring practical skills and towards preparing for future job markets:
- Internships. The LUMACSS internship programme provides initial professional experience in innovative firms (established companies or young fast-growing start-ups in the field of digitization).
- Capstone projects. These enable students to breathe life into their ideas and to carry these into actual practice. Examples include building a digital application or a Big Data tool, or devising an analytical solution for social media marketing. Capstone projects promote gaining hands-on experience with the tools and skills learned in theory, and thus enable students to experience digital challenges close-up (e.g. from data acquisition to analysis and reporting, or from application development to deployment and reporting).
Further information below
- Electives. The Practical Skills module enables students to specialize in particular areas through attending further LUMACSS courses.
Study plan for LUMACSS: see here
The LUMACSS program's Capstone Project (CP) offers the opportunity of an applied experience providing solid foundations for future graduates' professional portfolios and resumes. The experiential learning approach of the CP is particularly valuable for future graduates willing to develop their career in non-academic settings, such as future applied data analysts and Computational Social Scientists in governmental bodies, NGOs, or in the tech industry.
Capstone projects typically involve core digital skills like data mining, data analytics, visualization, machine learning, and web applications with a strong focus on developing data-driven solutions to real-world challenges. Using these skills, the capstone project allows LUMACSS students to turn their ideas into real solutions, demonstrating their competence, independence, and early achievements. A capstone project represents a culminating moment for LUMACSS students, and it is typically undertaken in the second year of the program. Typical deliverables include original data sets, data analytics reports, data visualizations, interactive web applications, project websites, policy reports, social media campaigns, and other data-driven applications.
LUMACSS students who are determined to undertake a capstone project will require and develop abilities such as planning, self-sufficiency, and goal setting and adjustment.
For further information on CP's regulations and examples for capstone projects click here
In addition to all the regular student mobility options open to all students of the Faculty of Humanities and Social Sciences at the University of Lucerne, students of LUMACSS can take advantage of a collaboration of LUMACSS with the programme “Data Analytics for Politics, Society and Complex Organizations” DAPS&CO at the University of Milan.
Most LUMACSS courses are taught in English. Students are therefore required to have a working knowledge of the English language. They must, however, also be proficient in German (Level C1 is recommended for both English and German).
Due to its strong focus on scientific methods, data analysis, digital skills and digitization, LUMACSS is suitable for students interested in pursuing a career in academia, data journalism, and/or market research and consulting. LUMACSS graduates will also have acquired the relevant skills to embark on a career in tech firms and/or think tanks.
Its interdisciplinary character means that LUMACSS is open to students from different educational backgrounds. Prospective students need to meet the following admissions criteria:
- University degree, Bachelor of Arts and/or Bachelor of Science
- Previous coursework, awarded at least 60 ECTS, in one or more of the following disciplines:
Computational Sciences, Economics, Law, Philosophy, Political Science, Sociology
Candidates holding a Bachelor’s degree in any other relevant discipline may also apply. Please direct any inquiries to the Programme Coordinator (firstname.lastname@example.org).
Depending on their previous education, candidates may be admitted on condition that they attend further (Bachelor) courses in addition to obtaining the 120 ECTS awarded for successfully completing the LUMACSS programme (conditional admission).
For further information on applications and admissions see here.
Regulations in German HS23
Regulations in English HS23
Regulations in German HS22
Regulations in English HS22
Regulations in German
Regulations in English
Musterstudienplan LUMACSS ab HS23
Musterstudienplan LUMACSS ab HS22
Musterstudienplan LUMACSS ab HS19
For further information on LUMACSS see our
Feel free to contact our
Nadia Bühler, MA
Department of Political Science
University of Lucerne; Frohburgstr. 3; P.O. Box 4466
Mondays to Thursdays: Room 3.A53, T +41 41 229 55 87
Appointments by prior arrangement