Data, Culture and Society MA

This module is intended to lay the theoretical and conceptual foundations when it comes to investigating and understanding how digital data and society intersect. The main focus of this module is on digital data practices and how they shape and are shaped by socio-cultural, political, economic and subjective factors. You will be introduced to key concepts and theoretical frameworks from a multidisciplinary perspective and engage with those during seminars and independent study. The assessment consists of a creative data project as well as a written essay.

This module introduces you to computer systems fundamentals and data systems fundamentals. The aim of the module is to ensure that you have a deep understanding of the high-level systems and software that support data storage and retrieval to be able to work with such systems and to be able to critically and confidently operate with system stakeholders and technical partners such as data providers, storage, and data processing actors. Concepts of computer systems and data creation, storage, and retrieval systems shall be introduced as well as compliance and security. This knowledge is reinforced by practical sessions where you will create, store and retrieve complex data using standard tools, as well as have the opportunity to analyse and critically evaluate typical real-world data lifecycle scenarios.

This module places an emphasis on different methods for researching AI, big data, datafication, social media and other practices and applications. This module is intended to provide an introduction at postgraduate level to the methodological tools for collecting, analysing and visualising digital data, both as an object of study and a means for analysis. The focus is on qualitative, quantitative as well as digital methods. The module consists of a range of lectures and seminars. You will also conduct a small group research project together that will make use of some of the tools and skills taught in the module.

This module provides the opportunity to undertake in-depth independent research into an aspect of data, culture and society. The module consists of a series of lectures and workshops, which will introduce you to the research process of their major projects. It includes guidance and tailored support. Building on what you have learned in the core and optional modules of the course, you'll conduct your own research project with guidance from a supervisor. This can either take the format of a 15,000 words dissertation, or a practical/creative artefact accompanied by a written report (extended academic rationale).

This module provides students with a theoretical understanding of the development, significance and contemporary uses of social media. It fosters both critical analysis and reflective practice in the networked digital media environment. Students will critically engage with key ideas of creativity, sharing and visibility in social media, and will participate in creative and reflective practice using leading social media tools and platforms. This will involve using social media tools to explore course concepts and theoretical materials by, for example, blogging about course readings, making an online video presentation to introduce a weekly seminar discussion, or making a photo essay in response to a key module theory. This module uses a flipped classroom approach through which informational content is made available to learners in advance of the on-campus class sessions, which are dedicated to discussion activities.

This module will introduce you to the political economy approach to analysing the production, distribution and consumption of media content in text and audio-visual form, whether online or offline, as well as the workings of telecoms networks behind online media. It identifies distinctive economic features of media and relates these to trends in the organisation of specific media industries, taking account of ways in which the economics of media have been affected by the spread of digital technologies.

This module will provide an overview of modern techniques in Machine Learning and Data Mining that are particularly customised for Data Science applications. You will be introduced to a range of toolkits, such as R and Python and they will explore the features and strengths of different machine learning and data mining methodologies, using selected data sets related to specific public sector or businesses application domains. Statistical knowledge is required in order to successfully complete this module.

This module introduces you to the theoretical frameworks and practices of the politics of global complexity, the debates that have been triggered, and the way that complexity understandings have developed, especially in the 1990s and 2000s. Emphasis is placed upon the conceptual frameworks deployed in understanding system effects on political, economic and social life and how these enable us to rethink governance, power and agency. While focusing on conceptual frameworks, this module also engages with how complexity is reflected in new approaches to policy, and external stakeholders will provide input to the module (for example, the Social Market Foundation, the New Local Government Network and the Foreign Policy Centre).

We are surrounded by artificial intelligence (AI) applications, whether we are aware of this or not. From personal assistants to automated news, from facial recognition technologies to self-driving cars, these are just a few examples of how AI is already impacting our lives. This module explains what AI is and offers a systematic overview of what is behind AI. It also looks into the controversies and challenges related to AI. The module teaches students to think critically about AI and assess the societal impact of AI. By mapping a broad range of applications, issues arising, and key debates, the module will equip students with a systematic understanding of current AI developments and their impact on society.

This module addresses one of the most urgent and, at the same time, elusive contemporary issues: the relationship between culture and the rise of digital media. It explores the production, circulation and cultural impact of digital technologies and considers how their emergence influences society, contemporary culture, and the relationship between the two. The module introduces key themes and debates in digital culture and explores ways in which digital environments impact upon how we produce, engage with, and thus understand their cultural formations.

This module introduces students to the main critical theories of digital media, and provides specific focus on the implications of race and culture on the development, infrastructures and ownership of digital media. This module has a particular interest in the power structures generated by geo-politics and fosters international knowledge of digital media. It uses readings and videos about the ways race, class and gender impact the production and circulation of digital culture and helps breaks down the popular mythologies about a placeless virtual reality and borderless digital culture. Whilst providing students with a theoretical and critical base, practical skills will also be developed through the making of a digital video artefact.

This module covers the theoretical and practical aspects of data visualisation including graphical perception, dynamic dashboard visualisations, and static data ‘infographics’. Tools such as R and Tableau are used. The aim is to prepare you for becoming a data visualisation specialist. Statistical knowledge is required in order successfully complete this module.

This module develops your skills and understanding of new emerging creative technologies particularly in extended and mixed reality solutions, through a digital (innovation) sandbox environment known as a Hackathon. Hackathons offer a means  for self-expression and creativity through technology.  Working with other students, you will experiment with key technologies as you develop a response to a real-world problem. You will gain the creative and technical skills needed to implement Virtual Reality, Augmented Reality and mixed reality projects that provide  innovative concepts and solutions to real world problems. The driving purpose of the module (innovation sandbox) is to allow you to build collaborative skills  through experience gained collectively in the real time act of problem solving, through research-informed practice.

This module involves working in a team with other students. Initially you will use the group as a brainstorming unit, bouncing digital media business ideas off each other as you go through the ideation process. Each group member comes up with one original digital media business idea, which you will individually submit as a lean feasibility study (formative submission).

Each team, based on the lecturer's feedback, then chooses the best/most feasible idea from the formative submissions. Working as a group, you will develop a business plan proposal for a new digital media start-up (CW1). For CW2 each student will individually pitch their group business plan to a panel of industry experts.