Semester 1
- Logic of Social Inquiry – Formulate social scientific research questions and design computational research to answer these questions.
- Behavioural Mechanisms in the Social Sciences – Review and critique the implicit and explicit assumptions about human cognitive and decision-making processes that underpin social scientific theories.
- Statistics and Data Science I – Explore key concepts, theorems, and distributions in probability theory and statistics, with an emphasis on stochastic computer simulations.
- Statistics and Data Science II - Estimate and interpret multivariate linear regression models, including extensions appropriate for causal inference.
Semester 2
- Discrete Choice Modelling - Apply statistical models for categorical outcomes that are integral to social network analysis, machine learning, and the analysis of human decision-making.
- Agent-Based Modelling – Develop and program Agent-Based Models (ABMs). Set-up and run experiments using ABMs for systematic theoretical inquiry.
- Social Network Analysis – Explore social network concepts, data structures, and measures, and apply statistical models to social network data.
- Digital Strategies for Social Science Research – Extract relevant information from online data sources, deal with the mass of extracted data, and apply appropriate tools for making sense of the data.
Semester 3
- Inequality and Segregation: Theory and Measurement – Learn about commonly used measures of inequality and segregation employed in social science research, and calculate the measures using real data and a computational approach.
- Organizations: Theory and Research – Review major theories, empirical research, and related literatures in the study of organizations including organizational demography, organizational decision-making, and internal dynamics.
- Culture: Theory and Research – Review major theories, empirical research, and related literature in the study of cultural production and cultural consumption, with an emphasis on contemporary research using computational designs.
- Big Data: Social Processes and Ethics - Examine the social processes involved in the creation, storage and use of large scale digital data sets and related ethical issues.
- Studies Abroad – Optionally study abroad during the third semester at a partner institution where you will acquire training in topics and methods related to your social scientific interests and within the programme’s scope.
Semester 4
- Master’s Thesis - Consult with a faculty advisor to devise research questions related to a topic of interest in the computational social sciences. Then perform original social research intended to answer these questions.