The Lucerne Master in Computational Social Sciences (LUMACSS) is an interdisciplinary programme that equips graduates with the knowledge and skills needed to tackle the main social challenges of the digital age. LUMACSS has been specially designed for two kinds of students: social science graduates seeking to strengthen their data analytics and digital computation skills; and computational sciences graduates eager to learn how to best apply their computation skills to social sciences data and research questions. LUMACSS provides a unique opportunity to combine the social sciences and the computational sciences. The programme offers in-depth teaching and research on digitization and its manifold effects on modern polities, societies and economies.

Programme

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.

Modules

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.

Courses include:

  • 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 (22 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.

Courses include:

  • 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.

Courses include:

  • 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 (16 ECTS) offers students three pathways towards acquiring practical skills and towards preparing for future job markets:

  1. 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).
  2. 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).
  3. Electives. The Practical Skills module enables students to specialize in particular areas through attending further LUMACSS courses.

Study plan for LUMACSS: see here and below

Courses and Lectures

In 2019, LUMACSS will allow access to the following courses taught at HSLU:

-          Introduction to R for Data Analysis

-          Multilevel/Hierarchical Modeling in R

-          Data Visualization in R

-          Introduction to Text Analysis in R

More information on our course offer can be accessed here:

Course catalogue (electronic version)

Course catalogue (PDF-Version)

Language Requirements

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).

Career Path

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.

Application and Admission

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 (samuel.huber@unilu.ch).

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).

Please note that the regular application deadline – for students who do not need a visa – for the 2019 autumn term has been extended to 31 August 2019.

For further information on applications and admissions see here.

Contact and Further Information

For further information on LUMACSS see our

Flyer on the Lucerne Master in Computational Social Sciences

 

Feel free to contact our

Programme Coordinator

Samuel Huber, 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 89
Fridays: Room 3.B10, T+41 41 229 55 95
samuel.huberremove-this.@remove-this.unilu.ch

Appointments by prior arrangement

And follow us on Facebook, Twitter and LinkedIn for regular updates.