Digital Strategies for Social Science Research

Spring 2024, Half-time, Norrköping

Semester Spring 2024
Place of study Norrköping
Pace of study Half-time
Level Second cycle
Teaching form On-Campus
Education Time Day-time
Education Language English
Course offering id LIU-46006
Period 202414 - 202423
Number of Places 5

Specific requirements

  • 180 ECTS credits passed including 90 ECTS credits in one of the following subject areas: social- and natural sciences, engineering, statistics, or mathematics
  • 15 ECTS credits in statistics, computer science, mathematics, or equivalent at advanced level
  • English corresponding to the level of English in Swedish upper secondary education (Engelska 6)
    Exemption from Swedish

Selection

Tuition fees

SEK 17600 - NB: Applies only to students from outside the EU, EEA and Switzerland.

If you have questions about the course, contact us

Etienne Ollion, course director

Madelene Töpfer, course administrator

Jonas Johansson, study adviser

Course syllabus

Digital Strategies for Social Science Research

Spring 2025, Half-time, Norrköping

Semester Spring 2025
Place of study Norrköping
Pace of study Half-time
Level Second cycle
Teaching form On-Campus
Education Time Day-time
Education Language English
Course offering id LIU-46006
Period 202514 - 202523
Number of Places 5

Specific requirements

  • 180 ECTS credits passed including 90 ECTS credits in one of the following subject areas: social- and natural sciences, engineering, statistics, or mathematics
  • 15 ECTS credits in statistics, computer science, mathematics, or equivalent at advanced level
  • English corresponding to the level of English in Swedish upper secondary education (Engelska 6)
    Exemption from Swedish

Selection

Tuition fees

SEK 17600 - NB: Applies only to students from outside the EU, EEA and Switzerland.

If you have questions about the course, contact us

Etienne Ollion, course director

Madelene Töpfer, course administrator

Jonas Johansson, study adviser

Course syllabus

This course introduces the theories and practices of digital social sciences. The course considers the respective relevance of various digital data sources (sensors, surveys, internet-based media platforms, etc.) for social scientific purposes. In hands-on computer labs, the functioning and structure of the World Wide Web and its mark-up languages are examined. Programming tools for extracting information from these structure, especially the manipulation of text and text files, are introduced. Finally, training in the use of common statistical and computational tools to explore and analyze data (descriptive statistics, dimensionality reduction, clustering) is provided, including a comparison between classic statistical methods and machine learning.