MC430      Half Unit
Data in Communication and Society

This information is for the 2021/22 session.

Teacher responsible

Dr Alison Powell


This course is compulsory on the MSc in Media and Communications (Data and Society). This course is available on the MPhil/PhD in Data, Networks and Society. This course is not available as an outside option.

Course content

This course investigates the significance of data in communications, social and cultural life. It introduces core theoretical perspectives on data and information from a social scientific perspective, 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? What ethical and governance questions pertain to the study of data as a socio-technical assemblage? 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.



This course is delivered through a combination of lectures and seminars totalling a minimum of 20 hours across Michaelmas Term. This year, some or all of this teaching will be delivered through a combination of online lectures and in-person classes/classes delivered online. This course includes a reading week in Week 6 of term.

Formative coursework

Students will be expected to produce 1 presentation (group project, student-led session) in the MT, along with written formative coursework. There are two options for written formative coursework on this course. Students can choose to submit either a 1500 word essay; or a 1000 word proposal for case analysis and recommendation

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 LT.

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

The project comprises of a case analysis and recommendation:

  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.

Course selection videos

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.

Student performance results

(2017/18 - 2019/20 combined)

Classification % of students
Distinction 37.2
Merit 35.9
Pass 21.8
Fail 5.1

Important information in response to COVID-19

Please note that during 2021/22 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the differing needs of students in attendance on campus and those who might be studying online. For example, this may involve changes to the mode of teaching delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.

Key facts

Department: Media & Communications

Total students 2020/21: 28

Average class size 2020/21: 13

Controlled access 2020/21: Yes

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