GV330 Half Unit
Data Science Applications to Politics Research
This information is for the 2025/26 session.
Course Convenor
Prof Melissa Sands
Availability
This course is available on the BA in Social Anthropology, BSc in History and Politics, BSc in International Social and Public Policy with Politics, BSc in Philosophy, Politics and Economics, BSc in Philosophy, Politics and Economics (with a Year Abroad), BSc in Politics, BSc in Politics and Economics, BSc in Politics and International Relations, BSc in Politics and Philosophy and BSc in Social Anthropology. This course is available with permission as an outside option to students on other programmes where regulations permit. This course is not available to General Course students.
This course is capped. Places will be assigned on a first come first served basis
Requisites
Pre-requisites:
Students must have completed GV101 before taking this course.
Additional requisites:
Students must have completed Introduction to Political Science (GV101) and either Research Design in Political Science (GV249) or an equivalent course (containing coursework in econometrics). Familiarity with R is also required.
Course content
The goal of this course is to introduce students to the latest empirical research using big data in political science. This course will cover different applications of big data in political science. For each, students will be introduced to the type of questions that each type of data can help answer and learn to apply the methods needed to analyse each type of data.
Teaching
15 hours of lectures and 15 hours of seminars in the Winter Term.
This course has a reading week in Week 6 of Winter Term.
Formative assessment
Presentation
Problem sets
Students will be expected to produce 1 problem set and 1 presentation in the WT.
Indicative reading
Brady, Henry E. "The challenge of big data and data science." Annual Review of Political Science 22 (2019): 297-323.
Gohdes, Anita R. "Repression technology: Internet accessibility and state violence." American Journal of Political Science (2020).
King, Gary, Jennifer Pan, and Margaret E. Roberts. "How censorship in China allows government criticism but silences collective expression." American Political Science Review 107, no. 2 (2013): 326-343.
Krupenkin, Masha. "Does partisanship affect compliance with government recommendations?." Political behavior 43, no. 1 (2021): 451-472.
Titiunik, Rocío. "Can big data solve the fundamental problem of causal inference?." PS: Political Science & Politics 48, no. 1 (2015): 75-79.
Assessment
Project (100%) in Spring Term Week 1
The coursework/project comprises a replication exercise, where students replicate and extend the analysis of one paper from a list of options.
Key facts
Department: Government
Course Study Period: Winter Term
Unit value: Half unit
FHEQ Level: Level 6
CEFR Level: Null
Keywords: Political Science, Data Science, Big Data
Total students 2024/25: 28
Average class size 2024/25: 14
Capped 2024/25: Yes(20)Course selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Personal development skills
- Self-management
- Problem solving
- Application of numeracy skills
- Specialist skills