SOC40760 Dynamic Social Networks

Academic Year 2020/2021

This module gives an introduction to the analysis of social networks. Topics include the visualization and statistical modeling of social networks. The module covers the theoretical foundation of these methods, but also gives hands-on instructions and examples for performing such analyses.

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Curricular information is subject to change

Learning Outcomes:

At the end of this module students will…
- understand the theoretical importance and relevance of studying networks
- have a good understanding of the theoretical foundations of various strategies for modeling network dynamics
- distinguish conceptually between social selection and social influence effects
- be able to handle social networks in R and conduct simple social network analyses

Student Effort Hours: 
Student Effort Type Hours


Specified Learning Activities


Autonomous Student Learning




Approaches to Teaching and Learning:
Student presentations; in-class discussions; critical writing 
Requirements, Exclusions and Recommendations
Learning Recommendations:

Prior knowledge of R and social network analysis is not required, but it is an advantage.

Module Requisites and Incompatibles
Not applicable to this module.
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: Lab assignment Varies over the Trimester n/a Graded No


Assignment: Response paper Unspecified n/a Graded No


Attendance: Participation Throughout the Trimester n/a Graded No


Presentation: Presentation Unspecified n/a Graded No


Carry forward of passed components
Resit In Terminal Exam
Summer 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?

Individual feedback is given to students after all assessment components