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 and engage in collaborative research projects to improve applied research methods, and propel such work into the future through suitable, robust, and ethical research infrastructure.
Social Data Science examines the methods for data-driven social sciences by integrating methods from data science with theories and concepts from the social sciences. We build strong competencies for analysing data for the government, organizations and private companies.
Applications range from questions of inequality, wellbeing, racial and ethnic relations, and diversity to what goes on in social media and digital platforms.
Our students learn both traditional statistical methods—exploratory and confirmatory—and what are often labelled as innovative approaches, such as machine learning, applications of artificial intelligence (AI), and network analysis. Beyond quantitative data, these methods can be used also to explore textual, audio, and visual materials.
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.
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: