MC430      Half Unit
Data in Communication and Society

This information is for the 2015/16 session.

Teacher responsible

Dr Alison Powell S119B


This course is compulsory on the MSc in Media and Communications (Data and Society). This course is available with permission as an outside option to students on other programmes where regulations permit.

This course is available to students on MSc programmes in Law, Sociology and Information Systems, with permission from their academic advisor and the course convenor.

Course content

This course investigates the significance of data in communications, social and cultural life. It introduces core theoretical perspectives on data, and outlines research approaches that take account of the contemporary influence of data within communication and society. The course begins with the social history of data, providing a strong baseline from which to analyse the contemporary position of data. The course will provide students with conceptual tools that will help unpack the logic of data, and train them to critically analyse phenomena such as big data, algorithmic regulation and augmented civic space. Its focus on contemporary issues allows an investigation of the politics and culture of data production, and the use of data as evidence in a range of fields including politics, advocacy and audience research.

Some of the questions addressed through the course include: Who owns data? Who makes data? Who makes sense of data? Is data public or private? How do different actors get access to data? How is data protected and regulated? These and other questions reflect the course’s focus on developing a critical account of how data is implicated in the structures that shape social life. Within these structures increasingly organised by algorithmic computation, how do people enact agency? How does culture both rely upon and push back against data-based communication?


10 hours of lectures and 10 hours of classes in the MT.

The provision outline of lecture topics for 2015-2016 is the following:

Week 1: Introduction: the Social History of Data

Block 1: Core Theories

Week 2: Social theory

Week 3: Information theory/STI

Week 4: Actor-networks, materialism and the posthuman

Block 2: Approaches and applications

Week 5: Philosophy and Sociology of data

Week 6: Political economy of data

Week 7: Big Data vs Social analytics

Block 3: Contemporary issues

Week 8: Surveillance/sousveillance/dataveillance

Week 9: Data and cultural representation (the state of the selfie)

Week 10: Data augmented spaces

Formative coursework

Students will be expected to produce 1 presentation (group project, student-led session) in the MT and either 1 essay or 1 project in the MT.

There are two options for written formative coursework on this course.

Students can choose:

EITHER a 1500 word essay

OR a 1000 word proposal for case analysis and recommendation

Students will also be assessed on 1 x group project: student-led seminar on one of the contemporary issues.

Indicative reading

Beer, D., & Burrows, R. (2013). Popular culture, digital archives and the new social life of data. Theory, Culture & Society 30(4), 47-71.

Boyd, D., & Crawford, K. (2012). Critical questions for Big Data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication & Society 15(5), 662-679.

Cheney-Lippold, J. (2011). A new algorithmic identity: Soft biopolitics and the modulation of control. Theory, Culture & Society 28(6), 164-181.

Gitelman, L., ed. (2013). ‘Raw Data’ is an Oxymoron. Cambridge, MA: MIT Press.

Kitchin, R. (2014). The Data Revolution: Big Data, Open Data, Data Infrastructures and their Consequences. London: Sage.

Lyon, D. (2014). Surveillance, Snowden, and Big Data: Capacities, consequences, critique. Big Data & Society 1(2), 1-13.

Mahrt, M., & Scharkow, M. (2013). The value of big data in digital media research. Journal of Broadcasting & Electronic Media 57(1), 20-33.

Russell Neuman, W., Guggenheim, L., Mo Jang, S., & Bae, S. Y. (2014). The dynamics of public attention: Agenda-setting theory meets Big Data. Journal of Communication 64(2), 193-214.

Tufekci, Z. (2014). Engineering the public: Big Data, surveillance and computational politics. First Monday 19(7).

Vaidhyanathan, S. (2006). Afterword: Critical Information Studies: A Bibliographic Manifesto. Cultural Studies 20(2-3): 292-315.


Assessment path 1
Essay (100%, 3000 words) in the MT.

Assessment path 2
Project (100%, 3000 words) in the MT.

There are two options for summative assessment on this course. 

Students can choose to write:  

EITHER a 3000 word essay

OR a 3000 word case analysis and recommendation. This comprises:1. Description of case 2. Analysis 3. Recommendations 4. Theoretical and normative contextualization

Case study analysis and recommendation: Students choose a current data-related product, service or use case, providing an analysis of how data are theoretically constructed, valued, managed and conceived within the project, using relevant theoretical material. The case study must identify an area of ethics, governance or social justice that this product, service or use case could improve, and provide a concrete set of recommendations, grounded in the existing theoretical, historical and empirical literature. This analysis and recommendation will be accompanied by a critical reflection that highlights the theoretical and normative aspects of the case, your analysis and your recommendation. This section should be grounded in the relevant theoretical material.

Key facts

Department: Media & Communications

Total students 2014/15: Unavailable

Average class size 2014/15: Unavailable

Controlled access 2014/15: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Self-management
  • Team working
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Commercial awareness
  • Specialist skills