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DRPS : Course Catalogue : Edinburgh Futures Institute : Edinburgh Futures Institute

Postgraduate Course: Text Remix (fusion on-site) (EFIE11004)

Course Outline
SchoolEdinburgh Futures Institute CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThis course will introduce some programming concepts and practice using text as data, and various transformation techniques and games as a means to stimulate creative skills. Further, the course will explore some of the ways that text can be algorithmically generated, or collected and then analysed.
Course description The course will explore practical creation and co-creation of text with human or computational partners. In particular, the course will concentrate on ways of categorising, transforming and responding to source text resulting in the creation of new experimental pieces or forms.

The practical work in the course will involve programming though Notebook-based worksheets. Students will therefore be introduced to some basic concepts and practice in computer programming using text as a data source to drive their exploration of these concepts. For example, one of the first tasks will be to replicate some simple text games to stimulate the creation of a new artwork.

The programming content will be built to include some simple automata (e.g. Markov chain text generator, twitter bot), and web scraping to obtain text data, and an introduction to some aspects of natural language processing. Lastly, these will cover some quantitative text analysis ideas, a discussion of qualitative analysis, and the concept of automated 'coding' will be demonstrated.

The Edinburgh Futures Institute will teach this course in a way that enables online and on-campus students to study together. This approach (our 'fusion' teaching model) offers students flexible and inclusive ways to study, and the ability to choose whether to be on-campus or online at the level of the individual course. It also opens up ways for diverse groups of students to study together regardless of geographical location. To enable this, the course will use technologies to record and live-stream student and staff participation during their teaching and learning activities. Students should be aware that:
- Classrooms used in this course will have additional technology in place: students might not be able to sit in areas away from microphones or outside the field of view of all cameras.
- Unless the lecturer or tutor indicates otherwise you should assume the session is being recorded.

As part of your course, you will need access to a personal computing device. Unless otherwise stated activities will be web browser based and as a minimum we recommend a device with a physical keyboard and screen that can access the internet.

Taught sessions will cover a mix of time spent on:
- Lectures/sharing of examples
- Text-based games
- Code-alongs
- Discussion and peer feedback on creative and coding tasks
- Group working and discussion
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Not being delivered
Learning Outcomes
On completion of this course, the student will be able to:
  1. Develop and implement simple text games and automata in a suitable programming language.
  2. Scrape text from various sources and conduct simple analyses using these as data.
  3. Generate new creative pieces using text and computational techniques as inspiration and input.
  4. Understand and be able to use critically some simple computational models for analysing a piece of text.
Reading List
Indicative reading list:

Acker, Amelia, and Joan Donovan. Data Craft: A Theory/Methods Package for Critical Internet Studies. Information, Communication & Society, vo.22, no. 11, Sept. 2019, pp. 1590-1609.
Bohnacker, H., Gross, B., Laub, J., & Lazzeroni, C. Generative Design. Princeton Architectural Press, 2012.
Clement, Tanya, and Amelia Acker, eds. Special issue on Data Cultures, Culture as Data. Journal of Cultural Analytics, Apr. 2019.
Graham, Elyse. The Republic of Games: Textual Culture Between Old Books and New Media. McGill-Queen's University Press, 2018.
Kac, Eduardo. Media Poetry an international anthology. Intellect, 2007.
Maeda, John. Design by Numbers. MIT press, 2001.
Odell, Jenny. How to Do Nothing: Resisting the Attention Economy. Melville House, 2019.
Shane, Janelle. You Look Like a Thing and I Love You. Wildfire, 2019, pp. 173-184.
Selby, A. (Ed.). Art and Text. Black Dog Publishing, 2009.

Web-based resources:
Language is a Virus:
Mark, A. 'How AI is radically changing our definition of human creativity'. Wired, 2019:
Marr, B. 'Can machines and Artificial Intelligence be creative?'. Forbes, 2020:
Ana Nicolaci da Costa. A. 'The pun-loving computer programs that write adverts.' BBC News, 2019:
Additional Information
Graduate Attributes and Skills Students will develop key knowledge skills through analysis of readings, presentations and the production of research material.
Students will use computational methods to address questions and issues of interest to researchers across a range of disciplines.
Students will develop original and creative responses using text as a source of data.
Students will communicate with peers and academic staff in a collegial setting, be introduced to a range of ICT applications to support and enhance work at this level, and will gain a grasp of basic programming concepts.
Working in small multidisciplinary teams, students will develop communication, autonomy, accountability and skills in working with others.
KeywordsText,data science,digital humanities,machine learning,natural language processing,creativity
Course organiserDr Stuart King
Tel: (0131 6)51 7032
Course secretaryMiss Katie Murray
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