Module Details

The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title Introduction to Computational Social Science methods
Code COMM742
Coordinator Dr E Musi
Communication and Media
Year CATS Level Semester CATS Value
Session 2021-22 Level 7 FHEQ First Semester 15


1. To provide students with basic methods to answer social science research questions through data analysis
2. To introduce students with skills to design and analyse quantitative surveys
3. To teach students how to collect and organise datasets from digital media sources
4. To give students insights on how to map and investigate social networks
5. To provide students with the empirical means to scaffold debates on online media at a large scale

Learning Outcomes

(LO1) Students will acquire broad foundational knowledge of research methods design, research philosophy and research ethics policy and practice.

(LO2) Students will learn how to design suitable surveys for different research questions.

(LO3) Students will acquire basic skills in probability analysis and statistical modelling for social science.

(LO4) Students will learn most up to date methodologies for data collection across digital media.

(S1) Data wrangling

(S2) Hypothesis testing through statistical modelling

(S3) Working with API (application programming interface)

(S4) Automated text analysis (sentiment analysis, topic modelling, opinion mining)



The module content will be delivered in three blocks of lectures. The first of these (weeks 1-4) is delivered to all PGT students registered on Communication and Media programmes and provides broad foundational knowledge required for research methods design, philosophy and pathway towards preparation of a research project proposal, which is the common assessment across all Communication and Media PGT programmes.

Week 1 – Introduction to module: 'what is research?'
Week 2 – Research methodologies: philosophical principles and frameworks
Week 3 – Research in practice: understanding primary and secondary research and analysis
Week 4 – Research ethics – issues, policy, best practice

BLOCK TWO (common with the MA in Media, Data and Society)
Week 5 – Survey design
Week 6 – Fundamentals of statistics
Week 7 – Independent study week
Week 8 – Fundamentals of pro bability

Week 9 – Data Collection from Digital Media
Week 10 – Fundamentals of social network analysis
Week 11 – Fundamentals of automated text analysis

Teaching and Learning Strategies

Summary of Learning and Teaching Methods:
Teaching method: workshop
This activity may be online or on campus and could be subject to changes.
Description: weekly lecture combined with interactive discussion
Schedule directed student hours: 24
Unscheduled directed student hours: 126
Attendance recorded: YES
Description of how self-directed learning hours may be used: reading module learning materials (key and suggested literature, lecture slides, additional reference material provided); assessment preparation

Teaching Schedule

  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours           24

Timetable (if known)              
Private Study 126


EXAM Duration Timing
% of
Penalty for late
CONTINUOUS Duration Timing
% of
Penalty for late
Testing different methodologies on a given dataset  -500 words         
Research project proposal  -2000 words    100       

Recommended Texts

Reading lists are managed at Click here to access the reading lists for this module.