GV222-5-AU-CO:
Fundamentals of Social Data Science
2025/26
Government
Colchester Campus
Autumn
Undergraduate: Level 5
Current
Thursday 02 October 2025
Friday 12 December 2025
15
11 March 2025
Requisites for this module
(none)
GV223
(none)
(none)
GV223
BSC LL20 Politics with Data Science
Social scientists learn about the society in large part by analysing empirical data. As we live in the era of big data where the enormous amount of data is generated every day and every second and available in unconventional way, we need new skills and knowledge to be able to effectively utilize these data to learn about new aspects of the world that have become accessible only recently. In this module, students will learn how to use facts and observations in the form of data to make inferences about the world. Rather than providing in-depth programming skill or statistical analysis, this module strives to inspire and enthuse students for the scientific endeavour and to widen the scope of knowledge and experience of diverse approaches using different types of data set to solve and address different social inquiries and problems.
Incorporating insights from behavioural, social and data sciences, the module will introduce how to address social scientific questions, how to approach and solve them using different types of data, the fundamental ideas and methods to analyse different types of data, and how to effectively communicate the process and insights with wider audience. Students will learn these through research examples and their own projects and exercises. Specifically, the seminars will focus on 1) learning basics on the data and methodological approaches for different types of data used in social science research, 2) understanding research process and data analysis through research examples, 3) discussing relevant methodological and other issues (e.g., ethics and privacy), and 4) managing and analysing data in lab sessions.
The aims of this module are:
- To familiarise students with foundations and applications of social data science.
- To raise students’ awareness of the potential and pitfalls of social data science.
- To equip students with the skills to understand and undertake social data science research.
By the end of this module, students will be expected to:
- To familiarise with foundations and applications of social data science.
- To develop original questions that will help make sense of the world.
- To identify data and resources that can help answering important questions about the world.
- To communicate ideas clearly and concisely to different audiences using data-driven evidence and insights.
The module’s weekly seminars cover topics such as, this is an indicative syllabus:
- Data in social science
- Reading and predicting social trends
- Mass survey data
- Experimental data
- Text as data
- Archival data
- Social network data
- Image and sound as data
This module will be delivered via:
- A weekly two-hour interactive seminar and lab session.
Students are expected to do the readings before the class, be prepared for lab exercises, and be ready to ask questions and actively participate in seminar discussions
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
Yes
Yes
No
No external examiner information available for this module.
Available via Moodle
No lecture recording information available for this module.
Government
* Please note: due to differing publication schedules, items marked with an asterisk (*) base their information upon the previous academic year.
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