Module description
Our experiences with online platforms, website, services and apps comes back to us in personalised ways. Whether it is our social media newsfeeds, Netflix profiles, Amazon recommendations, searches on Google, or even a tailored political ad, our data is increasingly shaping the content we encounter online. The aim of this module is to equip students with a body of knowledge and skills that will enable them to study the relationship between processes of datafication and the personalised ecosystems we now find ourselves embedded within. We will thereby explore how this relatively new phenomenon, which was initially propelled by the advertising and marketing industries, has spread to other areas of our everyday lives including but not restricted to business, politics, service industries, and healthcare.
The module will give students the opportunity to explore an array of theories and concepts which frame debates around datafication to unpack the unprecedented quantification of the self and the algorithmic practices through which it is transformed and monetised. Major debates surrounding the cultural, economic and political dimensions of personalisation will be discussed covering key aspects and characteristics involved in the relationship between material infrastructures, data extraction, privacy and personalisation. Given the contemporary focus of this module, some topics that could be covered include but are not limited to: datafication and social media, third parties, internet of things, applications, political campaigns, privacy, identity/subjectivity, and user experience.
Assessment details
1 x 4,000-word essay
Educational aims & objectives
Module Aims:
Provide a critical and historical overview of the relationship between our big social data and the personalisation of everyday life.
Synthesise contemporary research on big social data using theories from media and communication studies, cultural studies, and the digital humanities.
Critically examine the materiality of big social data; namely, the kind of data produced and its computational and algorithmic environment.
Learning outcomes
Through completion of this module students will:
Develop an advanced and systematic understanding of the main cultural, political, economic and material features of how social data relate to personalised digital ecosystems, alongside a strong command of related literature;
Assess critically the main interpretations propounded by different scholars on the major issues raised by digital culture and society as it relates to data and personalisation, and to design undertake substantial investigation into the similarities and differences therein;
Formulate and evaluate arguments and questions relating to broad issues around personalised digital ecosystems and digital culture and society.