University of Milan · Italy
Computational Social and Political Science
The Master's Degree Programme in Computational Social and Political Science (CSPS) equips students with the knowledge and skills to analyze political and social phenomena using computational and quantitative methods. It combines the hypothesis-driven approach of social sciences with the data-driven approach of data science, providing a robust repertoire for empirical analysis. Graduates will be able to design and conduct research projects, test hypotheses, analyze trends, and develop evidence-based proposals for interventions. The program focuses on using primary and secondary data, including surveys, social media data, and textual information, analyzed with statistical models, machine learning, and large language models. It also emphasizes causal inference and understanding the mechanisms behind complex socio-political outcomes.
Students receive extensive training in analytic methods, statistics, and computational science, with a focus on survey, experimental, and computational approaches. The curriculum includes computer programming, data management, and ethical considerations. Key topics cover multivariate analysis, machine learning, text-as-data, social network analysis, causal inference, and agent-based simulation models. Theoretical frameworks and qualitative insights are integrated to support the informed use of these modeling techniques.
The program involves practical training through individual and group projects using real-world data and case studies. Teaching methods are designed to foster the mindset of computational social and political scientists, enabling students to formulate testable hypotheses, link phenomena to models, design data collection procedures, map evidence, and evaluate the implications of their findings for decision-making.
