SOC41070 Sociological Thinking in the Digital Age

Academic Year 2023/2024

The ongoing digital transformation of our societies has had quite a few “biproducts”, among them is the unprecedented amount of transactional digital data that we produce as we go about our daily lives, also known as big data. Big Data are being used to study the very same digital transformation that led to their generation, as well as more general and fundamental aspects of our social lives in the framework of computational social science and beyond.
From the sociology point of view, a very first question to ask would be about the relevance of social theory to the “digitalized” study of humans. Some of the fundamental concept and theories in social studies were developed even before empirical sociology had become fashionable. Are those theories still relevant when machine learning is slowly becoming a common item in the toolset of social scientists? How social theory is being challenged, modified, and even ignored in our modern approach to studying humans and societies? How social theory can shape and motivate computational social science research? In this module, we seek to answer these questions through a short review of the main key concepts in sociology followed by an extended discussion on how they can be materialised and deployed in data-driven research through reviewing examples of successful and unsuccessful research programmes and analytical discussions.

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Curricular information is subject to change

Learning Outcomes:

Students who successfully complete this module should be able to:

• Define and recognise Big Data and their differences with the data generated in more traditional approaches such as surveys and interviews
• Understand the relevance of social theory to data-driven research
• Discuss the affordances and challenges in relation to materialising concepts central to social theory in the framework of data-driven research
• Outline the main modifications needed for a new framework of social theory that responds to a more solution oriented sociology

Student Effort Hours: 
Student Effort Type Hours
Lectures

24

Autonomous Student Learning

180

Total

204

Approaches to Teaching and Learning:
lecture; student presentations; in-class discussions; critical writing; 
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 In Module Component Repeat Offered
Essay: 3000 words essay on a set of pre-defined topics Coursework (End of Trimester) n/a Graded Yes

70

Yes
Presentation: Students will need to present short introductions to different concepts in each lecture Varies over the Trimester n/a Graded No

30

No

Carry forward of passed components
Yes
 
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?

Not yet recorded.

Name Role
Lucia Suchorova Tutor