Politics & International Relations - Politics & Data Science

The simultaneous development of cutting-edge data science methods to study digital text, audio, and video provide the tools we need to take advantage of these opportunities. The MSc Politics and Data Science is designed to equip students with the theoretical knowledge and methodological skills necessary to examine and understand politics in the digital age.

The MSc Politics and Data Science programme is organised around two streams of study. The first stream grounds students with backgrounds in political science and related social sciences in data science methods. The second stream is geared towards students with computer science or related technical backgrounds, teaching them about research design and theories in political science.

Apart from two required core modules in each stream, all students can select four optional modules that best fit their interests. These modules can either revolve around methods needed to study digital and digitised politics, such as programming and machine learning, quantitative text analysis, statistics, and experimental methods. Or they can be modules relating to comparative politics, international relations, political violence, political economy, and related fields that the School of Politics and International Relations has strengths in.

The programme thus provides a thorough grounding in political science and its sub-disciplines, and in-depth training in the empirical methods necessary to study important questions emerging in these areas of study.

Vision and Values Statement
The programme shall equip students with both the theoretical overview and the empirical tools necessary to understand and engage with the brave new world of digitised politics, and the expansion in scale, types, and complexity of data available to study political phenomenon. The MSc in Politics and Data Science provides students with in-depth knowledge of political science theories and approaches and the methodological training to apply these tools in a theoretically-informed manner. It offers advanced training in statistical and computational methods, including tools to extract and prepare unstructured data (data wrangling), to detect patterns and predict behaviour based on statistical data, to evaluate the veracity of theoretical models on large-scale datasets, to analyse highly interconnected data from networks and spatial data sets, and to develop simulations to evaluate the inherent consistency and implications of theoretical arguments.

Knowledge and understanding:
-Understanding the range of data science and machine learning methodologies that are available to data scientists, and their key advantages and disadvantages.

- Understanding of theories of political behaviour, political processes, and political institutions.

- Understanding variations in political systems and their functioning.

Applying knowledge and understanding:
- Understanding of central aspects of political and social science research design, such as conceptualization, operationalization and measurement.

- Ability to use knowledge of research design to systematically address questions pertaining politics and public policy.

- Gain general experience in applying data science techniques to questions of political and social science relevance.

Making judgements:
- Ability to decide on appropriate statistical techniques given a particular research question in relation to political behaviour and public policy.

- Ability to evaluate reported statistical and algorithmic results in political and social science research.

- Through training in general research design, ability to evaluate the veracity of input data of political and social behaviour for use in data science applications.

- Have a basic understanding of the situations where automated techniques as used in standard data science practice are suitable and ethically appropriate, and where not.

Communications and working skills:
- Ability to clearly communicate results from statistical analysis of political and social behaviour.

- Ability to communicate the possibilities and scope of data science tools for the understanding of political and social behaviour.

- Basic practice in team work and learning how to collaborate in larger technical projects, including ability to work with techniques for code sharing, agile development, tools for scientific replication, etcetera.

Learning skills:
- Have sufficient grounding in fundamentals of statistical analysis and computer science to be able to acquire new skills in data science.

- Have sufficient grounding in political and social science to be able to read into new domains of political and social science research.

Related Programmes
MSc Politics
MSc International Relations
MSc International Political Economy
MSc International Development
MSc Business Analytics
MSc Social Data Science

The MSc Politics and Data Science programme is organised around two streams of study. The first stream grounds students with backgrounds in political science and related social sciences in data science methods. The second stream is geared towards students with computer science or related technical backgrounds, teaching them about research design and theories in political science. Apart from two required core modules in each stream, all students can select four optional modules that best fit their interests. These modules can either revolve around methods needed to study digital and digitised politics, such as programming and machine learning, quantitative text analysis, statistics, and experimental methods. Or they can be modules relating to comparative politics, international relations, political violence, political economy, and related fields that the School of Politics and International Relations has strengths in.

Core and Option Modules for MSc Politics and Data Science Social Science Background Stream

These are the current modules for 2022/23 but are subject to change. Each of the following modules carries 10 credits unless otherwise specified.

Core Modules
POL40950 Introduction to Statistics (Autumn)
POL42340 Programming for Soc Scientists (Spring)
POL42350 Connected_Politics (Spring)

Core Option Modules - Select one
IS41210 Platform Governance (Spring)
IS41240 Social Networks Online&Offline (Spring)
POL42050 Quantitative Text Analysis (Spring)
SOC41070 SocThinking in the Digital Age (Spring)

Option Modules
Autumn
IS40840 Data & Society
POL40050 Theories of Internat.Relations
POL40140 Global Issues in Pol Theory
POL40950 Introduction to Statistics
POL40970 Politics European Governance
POL41020 Politics of Human Rights
POL41510 Middle East & North Africa
POL41650 Global Political Econ ofEurope
POL41800 Theories of Int'l Rels Stream2
POL41860 Governance, Pol, Dev 10cr
POL42040 Gender & the Political System
POL42440 Political Economy of Security
Spring

IS41210 Platform Governance
IS41240 Social Networks Online&Offline
POL40100 Politics of Development
POL40160 Comparative Public Policy
POL40370 International Political Econom
POL40540 Comparative European Politics
POL41030 Theory of Human Rights
POL41640 Qual Research Methods for Pol
POL41720 Gender, Peace, and Security
POL41780 The Politics of Inequality
POL41870 Pol Economy & Comparative Dev
POL41930 Psychology of Conflict in MENA
POL41980 Peace & Conflict Studies
POL42000 Political Theory and the EU
POL42050 Quantitative Text Analysis
POL42060 International Security
POL42340 Programming for Soc Scientists
POL42430 Social Theory & IR
SOC41070 SocThinking in the Digital Age
Please note, to be enrolled on POL42430 in Spring, students must have taken and passed either of the following two modules: POL41800 or POL40050.

Summer Trimester Core Module

POL42310 Thesis (30 credits)
Core and Option Modules for MSc Politics and Data Science Technical Background Stream

These are the current modules for 2022/23 but are subject to change. Each of the following modules carries 10 credits unless otherwise specified.

Core Modules?

POL42350 Connected_Politics (Spring)

Core Option Modules - Select one
IS41210 Platform Governance (Spring)
IS41240 Social Networks Online&Offline (Spring)
POL42050 Quantitative Text Analysis (Spring)
POL42340 Programming for Soc Scientists
SOC41070 SocThinking in the Digital Age (Spring)

Option Modules
Autumn
IS40840 Data & Society
POL40050 Theories of Internat.Relations
POL40140 Global Issues in Pol Theory
POL40950 Introduction to Statistics
POL40970 Politics European Governance
POL41020 Politics of Human Rights
POL41510 Middle East & North Africa
POL41650 Global Political Econ ofEurope
POL41800 Theories of Int'l Rels Stream2
POL41860 Governance, Pol, Dev 10cr
POL42040 Gender & the Political System
POL42440 Political Economy of Security

Spring
IS41210 Platform Governance
IS41240 Social Networks Online&Offline
POL40100 Politics of Development
POL40160 Comparative Public Policy
POL40370 International Political Econom
POL40540 Comparative European Politics
POL41030 Theory of Human Rights
POL41640 Qual Research Methods for Pol
POL41720 Gender, Peace, and Security
POL41780 The Politics of Inequality
POL41870 Pol Economy & Comparative Dev
POL41930 Psychology of Conflict in MENA
POL41980 Peace & Conflict Studies
POL42000 Political Theory and the EU
POL42050 Quantitative Text Analysis
POL42060 International Security
POL42340 Programming for Soc Scientists
POL42430 Social Theory & IR
SOC41070 SocThinking in the Digital Age

Please note, to be enrolled on POL42430 in Spring, students must have taken and passed either of the following two modules: POL41800 or POL40050.

Summer Trimester Core Module
POL42310 Thesis (30 credits)

Good undergraduate degree (2.1 or equivalent) in political science or related social science, or in computer science, statistics, or related discipline. Because of the streaming of the module structure of the program, we can accommodate students with a social science as well as students with a more technical background.

- Your application will be considered on its individual merits and relevant professional experience will also be taken into account.

English language requirements: applicants whose first language is not English should have met TOEFL, IELTs, or computer-based TOEFL requirements (600, 6.5, or 250 respectively), or the Cambridge English Test (Certificate in Advanced English at a minimum of Grade B, or Certificate of Proficiency in English at Grade C). Applicants who obtained a previous degree from an English-speaking university may be exempted from this requirement.

- These are the minimum entry requirements – additional criteria may be requested for some programmes.

How to apply?
The following entry routes are available:
MSc Politics & Data Science FT (W473)
Duration
1 Years
Attend
Full Time
Deadline
Rolling*

MSc Politics & Data Science PT (W474)
Duration
2 Years
Attend
Part Time
Deadline
Rolling*

* Courses will remain open until such time as all places have been filled, therefore early application is advised.

1 Year Full Time or 2 Years Part Time.

Careers & Employability
Graduates from this programme will be ideally equipped for careers in a large and varied set of employment sectors. The combination of a solid understanding of social science theory and the technical ability to apply advanced data-science approaches to answer questions of political and societal relevance, makes our graduates a unique addition to any data science team. Furthermore, graduates will be well-positioned to apply for quantitative social science PhD programmes with the aim of pursuing an academic career.

Potential future employers include:
Government
International Organisations (EU, UN, WTO, World Bank)
Non-Government Organisations
Not-for-profit sector
Corporate Sector
Tech industry
Think tanks

Potential roles include:
Political Advisor
Social Data Specialist
Data Manager
Chief Information Officer
Social Science PhD candidate