Learning objectives
The course aims to introduce the key methodologies and techniques that can be used to organise, explore, and analyse different types of cultural contents.
Prerequisites
Given the introductory nature of the course, no prior specific computer skills are required, apart from basic skills (e.g. use of a web browser and use of spreadsheets).
Course unit content
The course will be based on the presentation of theoretical concepts, an overview of important projects in the field of Digital Humanities, and practical activities.
In particular, it will focus on: (i) an introduction to Digital Humanities; (ii) distant reading and data visualisation; (iii) an introduction to automatic language processing; (iv) an introduction to Network Analysis.
Full programme
1) Introduction to Digital Humanities: definitions, topics, overview of some projects.
2) Basic concepts of computer science: algorithms, programming languages, internet, web, data. Description and evaluation of digital resources. Tools: Tesseract and GutenTag OCR online demo.
3) Introduction to the use of the command line for text manipulation. Using regular expressions to clean up data. Tools: command line (emulator for Windows) and Sublime Text.
4) The concepts of close reading, distant reading and scalable reading. Introduction to data visualization. Tools: ngram viewer, Voyant.
5) Introduction to the spatial turn in the humanities. Instruments: Recogito, Dariah GeoBrowser, Palladio.
6) Introduction to NLP, use of pipelines for language analysis, introduction to topic modeling. Tools: Tint, jsLDA.
7) Basic concepts of network analysis: structure, layout, basic metrics. Instrument: Gephi.
Bibliography
REQUIRED READINGS:
- Silvi D. e Ciotti F. (2021). Lezioni di Informatica umanistica. UniversItalia.
- Slides provided during the course.
- Moretti. F. (2011). Network theory, plot analysis. Pamphlet 2. Stanford Litarery Lab. URL: https://litlab.stanford.edu/LiteraryLabPamphlet2.pdf
- Ciotti, F. (2017). What's in a Topic Model? Critica teorica di un metodo computazionale per l’analisi del testo. Testo & Senso, n. 18. URL: https://testoesenso.it/index.php/testoesenso/article/view/370/pdf_227
- Salvatori, E. (2017). Digital (Public) History: la nuova strada di una antica disciplina. RiMe. Rivista dell'Istituto di Storia dell'Europa Mediterranea (ISSN 2035-794X), 57-94. URL: http://rime.cnr.it/index.php/rime/article/download/8/7
OPTIONAL READINGS:
- Jänicke, S., Franzini, G., Cheema, M. F., & Scheuermann, G. (2015). On Close and Distant Reading in Digital Humanities: A Survey and Future Challenges. In EuroVis (STARs) (pp. 83-103) URL: http://www.informatik.uni-leipzig.de/~stjaenicke/Survey.pdf
- Moretti, F. et al. (2019) La letteratura in laboratorio. A cura di Giuseppe Episcopo. FedOAPress, Napoli. URL: http://www.fedoabooks.unina.it/index.php/fedoapress/catalog/book/104
- Drucker, J. (2021). The Digital Humanities Coursebook, Routledge. URL: https://www.routledge.com/The-Digital-Humanities-Coursebook-An-Introduction-to-Digital-Methods-for/Drucker/p/book/9780367565756
Teaching methods
All lessons will take place in the computer room and include both a theoretical part and practical computer activities under the guidance of the teacher.
Assessment methods and criteria
The exam consists of two parts, both mandatory for all students: 1. Written essay (the subject of the essay must concern the application of at least one of the methods/tools seen in class; the essay, of maximum 5 pages according to a specific format for all and presented by the teacher, must be completed before the oral exam and delivered one week in advance of the exam to allow for correction); 2. Oral interview (on the essay, the topics presented during the course and the assigned bibliography). The final grade (between 18 and 30) is a weighted average based on the evaluation of the essay (50%) and of the oral interview (50). Any honors (lode) will also take into consideration the level of active and qualified participation during the lessons.
Other information
Attendance is strongly recommended. In any case, students unable to attend classes are strongly encouraged to contact the teacher at the beginning of the semester to decide on an alternative program.
2030 agenda goals for sustainable development
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