The Centre for Social Data Science (CSDS) advocates the use of data science methods and data-driven inquiry within the social sciences.

At the Centre for Social Data Science (CSDS), we cultivate data-intensive quantitative methods for a social-science-anchored response to the datafication and digitalisation of society. We aim to provide comprehensive and methods-focused teaching for students in the Contemporary Societies (COS) Masters Programme, engage in collaborative research projects in fields such as, demography, sociology, and social policy to improve applied research methods, and propel such work into the future through suitable, robust, and ethical research infrastructure. 

Methods and Applications

Social Data Science supports evidence-based decision making for the government, organizations and private companies. Some methodological examples include:

  • Statistical analysis to explore various topics, such as questions of inequality between and within genders, regions or generations. 
  • Dynamic probabilistic modelling in analyses involving forecasting and risk management. 
  • Machine learning methods for quantitative, textual, audio and visual materials.

We apply these tools to various data sources: surveys, interviews, register data, open governmental and business data, big data and digital trace data. However, essential focus in Social Data Science is to ground the data analysis in social science through its theories and concepts.

Our Ethics

It is vital that we don't forget the human underneath the data, and the importance of thoughtful deliberation of the effects of our research. For this reason, much of our projects and studies focus on inherent ethical quandaries in big data and analytical tools.

Support Services and Infrastructure

Our research infrastructural work began quickly after our centre was established in 2019. Some of the infrastructural work we have done, and continue to do, includes:

  • Methodological consultation for researchers in the fields of humanities and social sciences.
  • Frameworks for image labeling supported by the C. V. Åkerlund media foundation.
  • Text analysis in surveys with DARIAH and FIRI.
  • Hosting services such as LimeSurvey for the university community.