O que eu aprenderei?

The increasing integration of technology into our lives has created unprecedented volumes of data on everyday social behaviour. Troves of detailed social data related to choices, affiliations, preferences and interests are now digitally archived by internet service providers, media companies, other private-sector firms, and governments. New computational approaches based on machine learning, agent-based modelling, natural language processing, and network science have made it possible to analyse these data in ways previously unimaginable.

This is a chance to develop skills in computational techniques alongside a strong grounding in the principles and practice of contemporary social research. The programme’s quantitative methods training will help you harness complex data and use them to explore social theories and fundamental questions about societies. The programme’s theoretical and substantive training will introduce you to the principles of social inquiry and theories of human behaviour, and help you apply your technical skills to pressing social issues such as ethnic segregation in schools, income inequality, entrepreneurship, political change, and cultural diffusion.

During your first year you gain perspectives on the philosophy of social science, primers in the science of human decision-making, and frameworks for connecting individual behaviours to outcomes in social systems. You will also learn to apply advanced computational methods–including discrete choice modelling, social network analysis, agent-based simulation, and machine learning—to draw inferences about micro-level behaviours and macro-level outcomes.

With these building blocks in hand, you spend the third semester assembling critical knowledge of key theories and contemporary research in areas relevant to academic social science, government, and industry. During the third semester, you also have the option to study abroad at a partner institution.

In the final semester, you integrate the knowledge, skills, and theoretical approaches garnered in the first three semesters by writing a master’s thesis. As part of your thesis you conduct your own, original, computational research addressing a social scientific topic of your choosing.

Career opportunities

The dual skills you develop in social theory and data analysis are in high demand in public and private sectors. Graduates will be qualified for a number of roles: data analyst, marketing analyst, sales researcher, user experience researcher, policy analyst, etc. After graduation, you will also qualify for many PhD programmes.

Degree

Master of Science (120 credits) with a major in Computational Social Science

De qual departamento farei parte?

Faculty of Arts and Sciences

Opções de estudo

Período integral (4 semestres)

Valores
SEK 190,000 - NB: Applies only to students from outside the EU, EEA and Switzerland.
Data de início

Esperado Agosto 2020

Localização

Linköping University

Valla Campus,

LINKOPING,

SE-581 83, Sweden

Requisitos de admissão

Para estudantes do(s)/da Brasil

Other English Language Requirements: TOEFL (Paper-based) For English 6: Score of 4.5 (scale 1–6) in written test and a total score of 575.

Para estudantes internacionais

To meet the entry requirements for master's level studies, you must have been awarded a bachelor's degree (equivalent to a Swedish Kandidatexamen) from an internationally recognised university.

English Language Requirements:

  • IELTS (Academic modules) with an overall mark of 6.5, and no section below 5.5
  • TOEFL paper-based score of 4.5 (scale 1-6) in written test, with a total score of 575
  • TOEFL internet-based score of 20 (scale 0-30) in written test, with a total score of 90. Note - TOEFL Examinee Score Records are not accepted. All TOEFL tests must be sent directly from the Educational Testing Service (ETS).

Encontre o centro de IELTS mais perto de você e as datas da prova

Os requisitos para o IELTS podem variar de acordo com o curso que você escolher.

ADICIONAR AOS MEUS FAVORITOS