Social Data Science

Social data science is an emerging discipline that combines the methods of data science with the theoretical frameworks of the social sciences, asking how computational and statistical tools can be used to understand human behaviour, social structures, and collective phenomena. Where traditional social science relies heavily on surveys, interviews, and small datasets, social data science draws on digital trace data, large-scale administrative records, social media, and other data sources that have become available as social life has moved increasingly online. Where computer science is often more interested in building systems than in explaining social outcomes, social data science asks explicitly social and political questions.

The University of Exeter's three-year full-time Social Data Science programme sits at this productive intersection. You will study the quantitative and computational methods that make large-scale social analysis possible, including statistical modelling, machine learning, network analysis, and data visualisation, alongside the social science theories and research ethics that give these methods meaning and purpose. You will work with real datasets and learn to write code, developing the practical capability to collect, clean, analyse, and interpret social data, as well as the critical awareness to understand what data can and cannot tell us about the social world.

Exeter's reputation in social science research provides a strong intellectual foundation, and the programme includes a sandwich year, a year abroad, and a work placement, giving you substantial professional experience in data-relevant roles and international academic exposure.

A typical entry tariff of 152 points reflects the analytical demands of the programme.

Graduates pursue roles in data analysis, social research, government analytics, political consultancy, journalism, market research, technology policy, and NGOs, as well as postgraduate study in social science, data science, or public policy. The combination of social science literacy and technical data skills is increasingly valued across public and private sector organisations.