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IM904 Digital Objects, Digital Methods


20/30(CORE) CATS - (10/15 ECTS)

In the era of networks, big data and the digital turn, traditional objects, such as documents, pictures, data, groups, events or patterns, open up to new methods of research.

Emerging digital research methods also become means through which such objects are sustained, thus co-creating dynamic objects, such as networks, databases, platforms, data visualizations, maps and many other new forms of social, cultural and public life. This module offers an insight into these new and emerging societal and cultural entities and methodologies. We will take a number of digital objects relevant to the social sciences and humanities and analyse them using digital methods, including network analysis, software studies, content analysis, issue mapping, and others. Digital media research sits alongside social studies of computational technologies and cultural theory as the fields that emerging digital methods take inspiration from.

The module is open to students from all disciplines; no specific prior knowledge is required.

Module Convenor - Dr Nate Tkacz


For 20 CATS:

20% 1000-word scoping study presented in a group presentation and a report
on the project/presentation; 80% 3500-word essay.

For 30 CATS:

20% 1000-word scoping study presented in a group presentation and a report
on the project/presentation; 80% 5000-word essay.
(Students on the MA Digital Media and Culture must take the 30 CATS version of this

Indicative Syllabus

Week 1: Introduction to digital objects and methods

This session introduces students to recent debates about the role of digital methods in research and society. It discusses opportunities and challenges that the digital opens up for the configuration of the objects and methods of social, cultural and media research, and introduces key positions in the so called "digital methods" debate, which address fundamental questions such as: How does technology affect and inform how we research culture and society?

Week 2: Networks

This session focuses on networks as a digital object and method. Students are introduced to different methods for digital network analysis developed in social and cultural research and cognate fields, and then examines the possibilities that the digital opens up for the further development of these different approaches.

Week 3: Data

This lecture introduces a way of studying data from a cultural and social perspective. It considers what is socially and culturally at stake when data are disclosed, and explores a case study focused on the re-idenitification of persons using search engine data. We ask: what can data leaks teach us about the role of data in society and culture?

Week 4: Algorithms

This session will introduce students to algorithms as an object of social and cultural study. It will do so historically, formally and conceptually, and will reflect on the emergence of this digital object as a focal point of contemporary debates about automation, mechanical reasoning and obfuscation or blackboxing.

Week 5: Content

This lecture discusses emergent digital forms of content analysis, and explores their application in social and cultural research. We situate online research in this area in relation to wider methodological frameworks for the analysis of text and then examine the implementation of these approaches in online research: How do these methods structure relations between data capture, analysis and visualisation?

Week 6: Reading week

Week 7: Spaces

This lecture introduces cultural theories of space and discusses how software infrastructures challenge or alter existing spatial frameworks. We will reflect on the digital mediation of space in terms of cultural politics, economic valorisation, sociality and the emergence of publics.

Week 8: Events

This lecture discusses "the event" as an organizational form that is central to public, cultural and social life in digital media societies, and considers its rise to prominence as an analytic category in digital media research. We will explore challenges and opportunities that digital events pose for social, cultural and media research, such as their dynamic nature: when does an event begin and end? How to analyse a dynamic object, one of which the boundaries and composition constantly change?

Week 9: Controversies

This session turns to controversy analysis as a digital method. The lecture provides historical and conceptual background to situate the approach in relation to post-war methods developments like debate mapping and issue attention cycles (Downs, 1979). We discuss a set of empirical approaches for analysing controversies that were specifically developed for online and digital environments.

Week 10: Conclusion: methodological reflection and interdisciplinarity

The final lecture of the module will reflect on the presented material and explore some of the overarching concepts and concerns that are opened up by digitization, the operationalisation of methods and the pervasive networked character of today's world.

Ilustrative Bibliography
Fielding, N. R. Lee & G Blank (2008.) Sage Handbook of Online Research Methods (Thousand Oaks: Sage).

Fuller, M (2005). Software Studies: A Lexicon (Cambridge, Mass: MIT).

Gillespie, T. (2014). “The Relevance of Algorithms.” In Media Technologies: Essays on Communication, Materiality, and Society, Tarleton Gillespie, Pablo Boczkowski, and Kirsten Foot (eds), Cambridge: MIT Press, pp. 167-194.

Healy, K. (2011), The Performativity of Networks, European Journal of Sociology / Volume 56 / Issue 02 / August 2015, pp 175-205,

Herring, S. (2010) “Web Content Analysis: Expanding the Paradigm.” International Handbook of Internet Research. Eds. J. Hunsinger et al. Dordrecht: Springer. 233-249.

Lury, C. and N. Wakeford (2012). Inventive Methods: The Happening of the Social (London and New York: Routledge, 2012).

Marres, N. (2015) Why Map Issues? On Controversy Analysis as a Digital Method. Science, Technology & Human Values, 0162243915574602.

Mutzel, S. (2009) Networks as Culturally Constituted Processes: A Comparison of Relational Sociology and Actor-network Theory, Current Sociology 57(6): 871–887

Rieder, B. (2013). Studying Facebook via data extraction: the Netvizz application. In Proceedings of the 5th Annual ACM Web Science Conference. New York: ACM, 346-355,

Rogers, R. (2013) Digital Methods (Cambridge, Mass: MIT Press).

Ruppert, E., Law, J., & Savage, M. (2013). Reassembling social science methods: The challenge of digital devices. Theory, Culture & Society, 30(4), 22-46.

Thelwall, M., Sud, P., & Vis, F. (2012). Commenting on YouTube videos: From Guatemalan rock to el big bang. Journal of the American Society for Information Science and Technology, 63(3), 616-629.

Uprichard, E., R. Burrows, and Byrne, D. (2008). 'SPSS as an 'Inscription Device': From causality to description?' Sociological Review: Anniversary Issue - From causality to description, 56(4), 2008.

Venturini,T. (2012) “Building on Faults: How to Represent Controversies with Digital Methods.” Public Understanding of Science 21 (7): 796–812.

Learning Outcomes

  • to identify and analyse key methodological innovations that respond to the changing nature of research objects;
  • to reflect on the advanced debates across disciplines tackling new generations of methods dealing with digital change and to be able to creatively and independently evaluate and interpret existing scholarship and new methods;
  • to critically interpret and analyse new objects of research using advanced conceptual vocabulary and interdisciplinary innovative methods, both individually and in collaboration;
  • to produce independent research that practically applies some of the methods offered in the course of study, focusing on the new objects produced by digitization;
  • to demonstrate an ability for critical analysis and evaluation of current research and methodological innovation;
  • to demonstrate an ability to analyse new objects of research using interdisciplinary methodologies and new methods, individually and in groups;
  • to demonstrate an ability to formulate, plan, evaluate and conduct own independent research, making use of new and advances methods, some based on software applications or platforms.

Important Registration Information:

CIM Students

  • Please first discuss your optional module choices with you personal tutor during the personal tutor meetings and get their approval
  • Then complete and submit the optional module choice webform available in the CIM welcome page
  • The webform opens on 30th September at 14:00 BST and closes on 1st October at 15:00 BST
  • If there are any queries, please get in touch with Gheerdhardhini (PG Coordinator) via 

External Students

  • All external students - Please contact the CIM PG Coordinator (Gheerdhardhini) via email (, to request your optional module choice by Week 1 : Wednesday, 7th October, 17.00 BST.


  • Please be advised that you may be expected to have access to a laptop for some of these courses due to software requirements; the Centre is unable to provide a laptop for external students.
  • Please be advised that some modules may have restricted numbers and places are allocated according to availability.
  • Please note that a request does NOT guarantee a place on the module and is subject to availability.
  • Gaining permission of a member of CIM teaching staff or a member of staff from your home department or filling in the eVision Module Registration (eMR) system with the desired module does NOT guarantee a place on that module.
  • Requests after the specified deadline will not be considered.
  • CIM PG Coordinator will get back confirming your place in the module by 2nd October, Friday (For CIM students).
  • For external students - Only after confirmation of a place from CIM PG Coordinator can students’ or their home departments confirm their registration on eVision/MRM. Registrations by students who have not received confirmation of a place from CIM will be rejected via the system.

NOTE – The above-mentioned registration deadline also applies to the CIM optional modules running in Term 2. We will consider registrations again in the first week of Term 2, but only in relation to modules where there is availability.

We are normally unable to allow students (registered or auditing) to join/leave the module after the second week of it commencing.