IS41240 Social Networks Online&Offline

Academic Year 2022/2023

Social Networks Online and Offline: Spatializing Social Media introduces students to concepts, theories, and methods from social network analysis and their application to online and offline social networks. The module covers the rationale of social network analysis which states that relationships, more than individual and independent attributes, are critical to understanding social behaviour. The course is structured around the differences and similarities observed in online (e.g., social media activity) and physical social networks (such as family and friend relationships). Students will be introduced to a range of networks, including friendship networks, political discussion networks, social support networks, organizational networks, and online social networks. The module draws from Dr Bastos’ research mapping online social networks to geographically situated communities (Spatializing Social Media: Social Networks Online and Offline, Routledge: 2021).

The course aims are:
To introduce students to graph theory and social network analysis
To explore and visualize social variables that can be defined in terms of relationships as opposed to independent attributes
To provide an overview of physical social networks and their characteristics such as homophily, small-world properties, and clustering
Similarly, to provide an overview of the characteristics of online social networks such as scale-free distributions, polarization, algorithmic ranking, and echo-chamber communication
To provide an introduction to social network analysis tools and software, such as statnet, igraph, Gephi, and UCINET
To develop an understanding of how and under which circumstances online social networks can be mapped onto offline social networks

Knowledge and understanding:
On successful completion of this module, you will be expected to be able to:
Describe the fundamentals of graph theory and explain the role of relationships in studying social behaviour
Be familiar with seminal work in social network analysis and its applications
Have the capacity to explain how different network layouts can be transformed or converted into one another, e.g., edge lists, matrices, tables, lattices
Be able to describe and debate key issues cutting across online and offline social networks
Evaluate the limitations and challenges involved in mapping online to offline social networks

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Curricular information is subject to change

Learning Outcomes:

Upon completing the module, you will be expected to be able to:
Discuss and debate current issues of social network analysis and social media
Demonstrate clear written communication, oral communication, and presentation skills
Present, evaluate, and interpret relational data in connection to communication, sociological, and spatial theories
Make reasoned judgements and demonstrate a capacity for independent thinking
Access and utilise research resources drawing from social network analysis, sociology, communication, and spatial statistics in relation to social media and offline social networks
Critically describe the relationships between online and offline social networks, and how these sources of social activity can be mapped onto each other
Be familiar with methods to collect, retrieve, visualise, and analyse social network data online (e.g. social media platforms) and offline (e.g. institutional or intergroup affiliation)
Undertake accurate reading and clear written communication
Show self-reliance and the ability to manage time and work to strict deadlines
Evaluate complex arguments to critically assess practice and procedure

Indicative Module Content:

Week 01: Introduction to Social Network Data
Week 02: Introduction to Social Network Analysis
Week 03: Measures of Centrality
Week 04: Homophily and Communities
Week 05: Diffusion and Contagion
Week 06: Local and Digital
Week 07: Social and Spatial Networks
Week 08: Readership Online and Offline
Week 09: Physical and Online Networks
Week 10: Mapping Online to Offline Networks
Week 11: Protest Coordination Online and Offline
Week 12: Mapping Social Data

Student Effort Hours: 
Student Effort Type Hours
Lectures

24
Total

24
Approaches to Teaching and Learning:
The module takes a non-mathematical approach to social networks, but students will benefit from having been introduced to graph theory and computer routines for analysis and visualization of social networks.

Pre-requisites:
Background in sociology or social sciences, including anthropology, communication, economics, geography, information sciences, linguistics, political science, and psychology
Familiarity with algorithms and computational social sciences
Knowledge of graphs and familiarity with probability distribution and random variables
Familiarity with social media platforms such as Facebook, Twitter, and Instagram

Teaching pattern:
One 2-hours session combining lecture and tutorial (seminar discussion) per week across the full teaching term.
 
Requirements, Exclusions and Recommendations

Not applicable to this module.


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: Students will be assessed on the basis of one 3000-word piece of written coursework (portfolio of reaction papers or final coursework). Students may go over or under the limit by 10%. Coursework (End of Trimester) n/a Graded Yes

100

Carry forward of passed components
No
 
Remediation Type Remediation Timing
In-Module Resit Prior to relevant Programme Exam Board
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

Students may choose to write reaction papers addressing the weekly core readings. In that case, the reaction papers should be 300-word (students may go over or under the limit by 10%) addressing the set of assigned readings. Each of the reaction papers should include three parts: 1) a brief summary of each paper’s key points; 2) their strengths and limitations; 3) two to three questions that emerged from reading the set of papers. Students who choose to submit reaction papers should compile the 10 assignments into a portfolio of reaction papers and submit the material at the end of the module.