COMPUTATIONAL PHILOLOGY: DATA STRUCTURES AND ALGORITHMS

The course Computational Philology is part of the Master’s Degree in Digital and Public Humanities and is connected to the Venice Centre for Digital and Public Humanities (VeDPH) in the Department of Humanities. The course Computational Philology focuses on computational methodologies applied to philological disciplines with a weight of 6 ECTS credits.
The objectives of the course are:
— learning computational methods applicable to philological studies in the classical domain or in medieval, modern, and contemporary fields;
— acquiring skills for automatic text recognition from digital images, for extracting variants from automatically aligned texts, and for morphosyntactic and stylometric analysis of texts;
— acquiring competence in managing the workflow of digital scholarly editing, from acquisition via OCR/HTR to linguistic and stylistic analyses aimed to the constitution of the text;
— acquiring skills in the use and extension of philological digital resources through research infrastructures.

1. Knowledge and understanding:
• Knowledge of methods for evaluating similarity among texts
• Understanding of the principles of stemmatology
• Understanding of the principles of semi-automated linguistic analysis
• Knowledge of stylometry and semi-automated stylistic analysis

2. Applying knowledge and understanding:
• Ability to apply linguistic analyses to the evaluation of lectio difficilior
• Ability to apply stylometry to the detection of forgeries and stylistic analyses to the study of usus scribendi

3. Ability to rielaborate autonomously what has been learned:
• Ability to carry out complex textual analyses in new contexts
• Ability to develop critical thinking in choosing the most appropriate methods of analysis for the specific object of study

4. Communication skills:
• Ability to interact with peers and the instructor to communicate the results of research activities related to the course

There are no mandatory prerequisites, though a basic knowledge of XML-TEI text encoding is recommended.

The course Computational Philology allows students to explore key topics in philological studies, such as text similarity assessment or linguistic and stylistic analysis for variant evaluation, through the application of quantitative methods.
The course content includes computational methodologies applied to the domain of philological disciplines:
• Prompt engineering for the Digital Humanities
• Optical Character Recognition (OCR) and Handwritten Text Recognition (HTR)
• Evaluation of similarity among strings and complex objects
• Alignment algorithms
• Stemmatology
• Elements of semi-automated linguistic analysis
• Stylometry
• Elements of stylistic analyses with computational tools
• Domain-Specific Languages (DSLs) for text encoding and annotation
• Processing of documents encoded through DSLs
• AI-driven textual restoration
• Major research infrastructures for the Digital Humanities (CLARIN, DARIAH, E-RIHS, and OPERAS)
• FAIR Data, Linguistic Linked Open Data, and Philological Linked Open Data in the CLARIN ecosystem

All texts and learning materials will be made available on Moodle.

Evaluation will be based on the following components:
Final oral exam (mainly focused on the project and topics discussed in class)
Participation in discussions and activities
In-class presentation

oral

Below 18: exam failed – insufficient knowledge and understanding of course topics – insufficient performance in class and homework
18–21: sufficient knowledge and understanding – sufficient performance
22–24: satisfactory knowledge and understanding – satisfactory performance
25–27: good knowledge and understanding – good performance
28–30: very good to excellent knowledge and understanding – very good to excellent performance

Attendance is strongly recommended.
Students will work on a shared project with individual subprojects, which they will discuss during the final exam.
Teaching methods include lectures, lab activities, presentations, and discussions.
A guest lecture will be included when possible.

Accessibility, Disability, and Inclusion
Support and accommodation services for students with disabilities or specific learning disorders:
Ca’ Foscari complies with Italian law (Law 17/1999; Law 170/2010) regarding support services and accommodations for students with disabilities or specific learning disorders.
If you have a motor, visual, hearing, or other disability (Law 17/1999), or a specific learning disorder (Law 170/2010), and require support (classroom assistance, technological aids for exams, personalized exams, accessible materials, note-taking support, specialized tutoring, interpreters, etc.), please contact the Disability and DSA Office: disabilita@unive.it

This subject deals with topics related to the macro-area "Cities, infrastructure and social capital" and contributes to the achievement of one or more goals of U. N. Agenda for Sustainable Development