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CSOC20010

Academic Year 2024/2025

Applied Computational Social Science (CSOC20010)

Subject:
Computational Social Science
College:
Social Sciences & Law
School:
Sociology
Level:
2 (Intermediate)
Credits:
5
Module Coordinator:
Dr David Anzola
Trimester:
Autumn
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

This module expands on the contents of CSOC10010 by providing students with a hands-on critical introduction to the professional practice of computational social science. Two methods: agent-based social simulation and network analysis, will be used to reflect on: (i) the institutional and conceptual differences between computational social science and mainstream social and computer science, (ii) the current and future computational social science labour market, (iii) the knowledge and skills involved in the professional practice of computational social science, and (iv) the impact of the progressive digitalisation of society and the advances in computation.

About this Module

Learning Outcomes:

On completion of this module, students will be able to:
• Identify basic methodological features of agent-based social simulation and network analysis.
• Manipulate code and parameters in computational models.
• Critically reflect on the determinants of performance in tasks relying on computational methods.
• Assess the methodological and theoretical competence required in their professional pathway

Student Effort Hours:
Student Effort Type Hours
Autonomous Student Learning

104

Lectures

24

Total

128


Approaches to Teaching and Learning:
- Lectures
- Group work
- Active/task-based learning
- Critical writing
- Reflective learning

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Pre-requisite:
CSOC10010 - Intro Comp Soc Sci


 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Assignment(Including Essay): Written assignment reflecting on the representational capacity of digital technologies and the (digital) data challenges in contemporary society. Week 8 Standard conversion grade scale 40% No
50
No
Student Negotiated or Choice of Assessment: Video (individual) reporting the findings of a co-word analysis
OR
Podcast (two people) discussing the professional -computational- skills set demanded by the contemporary workplace.
Week 12 Standard conversion grade scale 40% No
50
No

Carry forward of passed components
No
 

Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Autumn Lecture Offering 1 Week(s) - 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12 Mon 12:00 - 12:50
Autumn Lecture Offering 1 Week(s) - 1, 2, 3, 4, 5 Wed 11:00 - 11:50
Autumn Lecture Offering 1 Week(s) - 6, 10, 12 Wed 11:00 - 11:50
Autumn Lecture Offering 1 Week(s) - 7, 9, 11 Wed 11:00 - 11:50