Introductory description

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 web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

Week 1: Introducing Digital Methods. This session introduces students to recent debates about the role of methods in research, culture and society. It discusses opportunities and challenges that the digital opens up for the roles that digital objects and methods play in social, cultural and media research, and introduces the so called "digital methods" debate, addressing fundamental questions such as: How does media technology affect how we research culture and society? Has digitization given rise to 'natively digital' objects and methods? Does the digital make possible new approaches to how we assemble methods, objects and techniques in research and social, cultural and public life?

Week 2: Search. Querying search engines has become a widespread common practice around the globe, and many platforms have integrated dedicated search or 'information retrieval' features as part of their service provision. In an information landscape often described in terms of 'overload', search engines' ostensive goal is to order information and make it easily accessible. As mediators of access, search engines play a crucial role in culture; they act as gatekeepers, curators, or filterers of our informational realities. Search engines are a topic of research in their own right, but they have also been repurposed to help conduct social and cultural research. This week will explore the possibilities of search as a method, or 'search as research', as Richard Rogers puts it. We explore how search queries can be used to study the 'medium' of search engines and their interfaces, as well as how it has been used to 'ground' more explicitly social and cultural inquiry.

Week 3: Networks. This session offers an introduction to networks as a digital object and method. The lecture introduces three different methods for digital research on networks developed in social and cultural research and cognate fields: social network analysis, actor network theory and issue network research. We then examine the possibilities that the digital opens up for the further development of these approaches to network analysis. Students will be introduced to the idea of medium-specific network analysis, through an exploration of hyperlink analysis.

Week 4: Comments. From early bulletin boards, discussion forums, and blogs, to the social media platforms that dominate contemporary digital cultures, the internet has fostered the rise of a 'participatory' media landscape. Indeed, the participatory quality of digital, networked media are one of the ways these media were defined against older 'broadcast' media. But, all participation is not created equal. This week, we consider what has been described as 'the bottom half of the web': comments. Comments are one of the main things that people do online; they are often informal, 'vernacular', and common across many platforms. They give voice to the ordinary, the intimate, as much as they often reveal the uglier sides of human nature. The technical and cultural specificity of different digital platforms also gives rise to unique 'comment cultures', with distinct norms, aesthetic sensibilities that become available for digital research through different types of textual and content analysis. This lecture introduces students to the academic study of comments and shows a number of current ways they are approached methodologically.

Week 5: Content. In the last session, we explored 'comments' as a particular kind of digital object. While a form of content in their own right, comments have often been defined against the 'main', 'official' or 'influential' content that features on the web. This week we extend the discussion to consider digital content in general and tie this to the research tradition of content analysis. As we shall see, digital content can be highly diverse in terms of subject matter, media form(at) and 'technicity'. We will therefore focus on approaching content with sensitivity to the platform dynamics and cultures within which content is produced.

WEEK 6: READING WEEK

Week 7: Images. This week marks a shift away from text-based methods and objects to visual, image-based media. From the circulation of memes on image boards and alternative forums to aesthetic cultures fostered by dedicated image platforms such as Instagram, images feature prevalently in digital cultures. Digital images have generated their own distinct aesthetics and vernaculars - such as selfies, memes and image macros, and glitch - which derive, in part, from the technical specificity of digital images and the platform conditions within which they circulate. Such images can be studied in a number of distinct ways, as data objects, as things reflecting platform dynamics, as visual/semiotic forms, and so on. This week, we introduce a number of ways to think about images as digital objects; how such images can be studied in their own right, or within a larger research project.

Week 8: Measure/Rank. Digital cultures contribute significantly to society's 'datafication'. This week we look more closely into the cultural practices, objects and methods that result from widespread datafication and the use of algorithms. We will look at two closely related things: measures (or metrics) and ranks. Both are productive of digital objects, such as the total number of shares, likes, favs, followers, and so on, or top ten lists, most read articles, or the creation of a newsfeed. Both are also methods. We reflect on the role of measure and rank in digital culture, as well as how they can be used for research.

Week 9: People/Traces. This week we will examine ethnographic methods and some of the ways in which they can be turned to the study of digital objects. Ethnographic methods were developed for the study of human culture and social life, and are one of the principle methodologies used for qualitative social research. We will reflect on what we may learn from this history about wider methodological issues, in particular the role of data in research and the role of first-hand understanding. We will also consider the future of the method, and competing adaptations of ethnographic approaches for the study of digital objects. We will also reflect on the role of methods such as ethnography in the development of digital technologies, through their adoption as part of the toolkit of design, and the interesting ways that methods can become an object of study in their own right.

For the seminar, students will need to read two texts. The first is the introduction to Horst and Miller’s influential book ‘Digital Anthropology’. The second is the development of a method Geiger and Ribes have named ’trace ethnography’. Students should prepare by carefully examining how each text sets out a methodological problem, how they argue for their particular agenda, and what differences they imply for what ‘doing a digital ethnography’ would entail and what kind of object of study it might have.

Conclusion: Thinking Methodologically. The final session will reflect on and pull together the overarching themes of the module. At this stage, all students will have explored a number of digital objects and methods across different platforms. This lecture will focus on the question of how to think 'methodologically', focusing on questions of inventiveness, media dynamism and hybrid forms of expertise (and related research).

Learning outcomes

By the end of the module, students should be able to:

• demonstrate an ability for critical analysis and evaluation of current research and methodological innovation;
• demonstrate an ability to analyse new objects of research using interdisciplinary methodologies and new methods, individually and in groups;
• 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;
• demonstrate an ability to identify and analyse diverse areas of practice, using interdisciplinary concepts and methods, in creative, self-led interpretative research;
• demonstrate an ability to formulate and plan research, delegating research tasks and evaluating the cohesion of a research project.

Indicative reading list

• Amoore, Louise. Cloud Ethics: Algorithms and the Attributes of Ourselves and Others. Durham: Duke University Press, 2020.
• Bucher, Taina. If...then: Algorithmic Power and Politics. Oxford University Press, 2018.
• Burrows, Roger, and Mike Savage. ‘After the Crisis? Big Data and the Methodological Challenges of Empirical Sociology’: Big Data & Society, 1 April 2014.
• Chun, Wendy Hui Kyong. Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition. Cambridge, Massachusetts: The MIT Press, 2021.
• Dieter, Michael, Carolin Gerlitz, Anne Helmond, Nathaniel Tkacz, Fernando N. van der Vlist, and Esther Weltevrede. ‘Multi-Situated App Studies: Methods and Propositions’. Social Media + Society 5, no. 2 (1 April 2019).
• Fuller, Matthew. ‘Software Studies Methods’. In The Routledge Companion to Media Studies and Digital Humanities, Routledge, 2018, pp. 250–57.
• Gillespie, T, Boczkowski, P J and Foot, K A, eds. Media Technologies: Essays on Communication, Materiality, and Society. Cambridge MA: MIT Press, 2014.
• Lindgren, Simon. Data Theory: Interpretive Sociology and Computational Methods. 1st edition. Polity, 2020.
• Lury, Celia. Problem Spaces: How and Why Methodology Matters. Cambridge, UK: Polity, 2020.
• Marres, Noortje. Digital Sociology: The Reinvention of Social Research. Malden, MA: Polity, 2017.
• Noble, Safiya Umoja. Algorithms of Oppression: How Search Engines Reinforce Racism, New York: New York University Press, 2018.
• Rieder, Bernhard. Engines of Order: A Mechanology of Algorithmic Techniques. Amsterdam University Press, 2020.
• Rogers, Richard. Doing Digital Methods. London: SAGE Publications, 2019.
• Schäfer, Mirko Tobias, and Karin Es, van, eds. The Datafied Society. Studying Culture through Data. Amsterdam University Press, 2017.
• Venturini, T., & Munk, A. K. Controversy Mapping: A Field Guide. Malden, MA: Polity, 2021.

Interdisciplinary

Students are required to reflect on advanced debates on digital change across a range of disciplines, and to critically interpret and analyse new objects of research using innovative interdisciplinary methods.

Subject specific skills

• 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;
• to demonstrate an ability to identify and analyse diverse areas of practice, using interdisciplinary concepts and methods, in creative, self-led interpretative research;
• to demonstrate an ability to formulate and plan research, delegating research tasks and evaluating the cohesion of a research project.

Transferable skills

• to use a variety of software applications and knowledge on technical aspects of data to analyse new objects of research;
• to use web tools to produce a log;
• to work effectively as part of a team, giving and receiving feedback, discussing and expressing opinions and exploring methods practically, individually and in groups;
• written and oral communication skills: to articulate arguments orally and through well-argued essay writing, supported by wide reading, research and methodological practice;
• work together with others;
• manage time to meet a series of deadlines;
• make productive links between theoretical ideas and practical phenomena and choose methodologies best suitable for study of particular objects;
• solve unusual problems creatively by using original and innovative methodologies.