Big Data in Culture and Society at King's College London, University of London - UCAS

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Course summary

Our Big Data in Culture & Society MA recognises the growing importance of Big Data in contemporary society and addresses the theory and practice of Big Data from an arts and humanities perspective. What is Big Data? Beyond the unprecedentedly large data sets that can be analysed to reveal patterns, trends, and associations, it is increasingly about our everyday lives. In short, it is about how the data we generate is transforming social, cultural, political and economic processes as well as the generation of knowledge. This course is likely to appeal to a broad range of students across the Arts and Humanities from Sociology to Political Science to English to Business and beyond. It will attract forward-thinking students interested in emerging trends who recognise that data scientists and analysts require collaborators with domain specialisation and critical insights. This Big Data in Culture & Society MA offers you the opportunity to develop your knowledge and understanding of the role of Big Data in culture and society. It will enable you to analyse Big Data across social, political and economic areas. In addition to the required content we cover, you will have the opportunity to pursue your own academic interests through our optional modules and to undertake an internship and a group project module. By bringing together domain knowledge and technical skills and approaching these from an Arts and Humanities perspective, the course will help you develop highly valued employment skills and expertise for careers in Big Data. The course will provide you with: Knowledge and understanding of the effects of Big Data on contemporary society. Critical and theoretical approaches to the analysis of Big Data. Knowledge of the historical antecedents of Big Data. Understanding of the innovative methods for generating new knowledge through the use and analysis of Big Data. Understanding of Big Data in relation to the broader study of digital culture, the digital humanities and traditional humanities disciplines. Understanding of appropriate personal and professional conduct in the context of digital culture as an emerging discipline. Course purpose The MA Big Data in Culture and Society offers students the opportunity to develop their knowledge and understanding of the role of Big Data in culture and society. It enables them to analyse Big Data across social, political and economic areas and provides them with a background for pursuing careers in Big Data by bringing together domain knowledge and technical skills. Key Benefits Taught by scholars working at the leading edge of digital studies and Big Data. Offers a lively mix of theory and practical work. Equips students with skills that are highly attractive to employers in our digital age. Provides a series of workshops with data scientists and analysts to learn collaborative practices and applications in social media and cultural analytics, mobile platforms, and data visualisation. Is at the forefront of digital developments - Big Data is transforming society, politics, the economy and culture and impacting work Offers innovative interdisciplinary methods of study crossing technological and cultural perspectives Links Big Data to Culture, Law & Ethics, Geography, Public Health, and Social Life Located in a highly ranked department - the Digital Humanities department was ranked first in the UK for research power (2014 Research Excellence Framework)


Courses are divided into modules. You will normally take modules totalling 180 credits. You are required to take: • Theorising Big Data (20 Credits) • Big Data in Practice: Co-laboratories, Tools and Methods (20 Credits) • From Data to Insight – Cultural and Social Analytics (20 Credits) • Big Data and the Law: Foundations, Regimes and Principles, Challenges (20 Credits) • Dissertation (60 Credits) Optional Modules In addition, you are required to take two modules totalling 40 credits from a range of optional modules that typically includes:Digital Arts and Culture (20 Credits) • Digital Arts and Culture (20 credits • Editorial models for Digital Texts: Theory & Practice (20 credits) • Web Technologies (20 credits) • Digital Publishing (20 credits) • Communication & Consumption of Cultural Heritage (20 credits • Material Culture of the Book (20 credits) • Applied Visualisation for Cultural Heritage (20 credits) • Open Culture (20 credits) • Ontologies of Digital Media (20 credits) • Social Media: Protest & Political Campaigning (20 credits) • From Information to Knowledge – Metadata & Systems for Digital Assets & Media (20 credits) • Management for Digital Content Industries (20 credits) • Digital Media, Digital Marketing (20 credits) • Curating & Preserving Digital Culture (20 credits) • Crowds & Clouds – Digital Ecosystems (20 credits) • Internship (20 credits) • Up to 20 credits from master’s modules offered in the Faculty of Arts & Humanities, subject to approvals. King’s College London reviews the modules offered on a regular basis to provide up-to-date, innovative and relevant courses of study. Therefore, modules offered may change.

Assessment method

We assess our modules entirely through coursework. This will comprise a mixture of essays, project work, and workshop reports, depending on the modules you choose.

Qualified teacher status (QTS)

To work as a teacher at a state school in England or Wales, you will need to achieve qualified teacher status (QTS). This is offered on this course for the following level:

  • Course does not award QTS

Entry requirements

Bachelor's degree with 2:1 honours in an English, Arts, Humanities or Social Science degree, or a related discipline.

Fees and funding

Tuition fees

EU £9990 Year 1
England £9990 Year 1
Northern Ireland £9990 Year 1
Scotland £9990 Year 1
Wales £9990 Year 1
International £26550 Year 1

Additional fee information

No additional fees or cost information has been supplied for this course, please contact the provider directly.
Big Data in Culture and Society at King's College London, University of London - UCAS