Research Design for Social Data Science

About

This course introduces students to conceptual and methodological aspects of social science research designs, including both quantitative and qualitative methods. Research methods covered include historical context, social science methods, data science techniques, experimental and survey designs, considerations about causality, and measurement.

The course emphasises how different designs for collecting and analysing data strengthen social science arguments and enhance their causal credibility.

Learning objectives

• Understand the structure of scientific work, including the role of concepts, hypotheses, and theories
• Understand how to integrate theory and methods
• Understand how qualitative data can sharpen understanding of causal mechanisms and arguments
• Understand how online generated data can be used to model human behaviour
• Understand the limits and strengths of experimental, quasi-experimental, and non-experimental designs.
• Understand why design is key to strengthen science arguments
• Understand the issues involved in making causal arguments

Weekly topics

Week 1 – The Origins of Science
Week 2 -Doing Social Science
Week 3 – Causality Part 1: Causal Relationships

Week 4 – Causality Part 2: Endogeneity
Week 5 – Experiments

Week 6 – Surveys
Week 7 – Data Science Methods
Week 8 – Online Data and Metrics