Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

Study Plan

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.

CURRICULUM TIPO:

1° Year 

ModulesCreditsTAFSSD
One module among the following (philology must be related to one of the chosen languages)
6
B
L-FIL-LET/09
ModulesCreditsTAFSSD
One module among the following (philology must be related to one of the chosen languages)
6
B
L-FIL-LET/09

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S010863

Credits

6

Language

English en

Scientific Disciplinary Sector (SSD)

L-FIL-LET/14 - CRITICAL COMPARATIVE LITERATURE

Period

II semestre (Lingue e letterature straniere) dal Feb 13, 2023 al May 27, 2023.

Learning objectives

In this course students will learn computational methods that can be applied to conduct linguistics and literary studies. These computer-assisted methods (c.f., Scalable and Distant Reading) support the systematic analysis of larger and larger amounts of textual data, enabling literary investigations beyond what feasible with solely human effort. At the end of the course students: - will learn how to approach and conduct the analysis of a text using computational methods - will be able to understand the basic principles, the practical aspects, and the main limitations of some computational methods enabling text analysis, data mining, and data visualization

Prerequisites and basic notions

None

Program

The course will provide an overview of the main approaches in computational literary studies, by taking into consideration both theories, methodologies, and applications. Main topics of the course will be:
- the “distant reading” paradigm
- operationalization and modeling of literary theories and phenomena
- text analysis approaches (e.g., stylometry, sentiment analysis, topic modeling)
- text visualization approaches (e.g., maps, plots, and networks)
- machine learning and text classification
All approaches will be presented by highlighting both their advantages and limitations, thus inviting students to participate in a critical discussion of the past, present, and (possible) future of computational literary studies.

Bibliography

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Didactic methods

Teaching modality will involve frontal lessons and discussions of selected papers. Students will also be invited to participate in seminar-like activities.

Learning assessment procedures

The exam will be divided into two parts. For attending students, the first part of the exam will consist in the evaluation of in-class interaction (participation in shared readings and seminar discussions). The second part will consist in the redaction of a small speculative project concerning the possible application of computational methods in literary studies. The project will have to be submitted in advance and will be discussed during the exam. For non-attending students, the first part will be replaced by an interrogation on the course topics.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Evaluation criteria

Students will have to show that they have gained critical skills during the course, by means of analytical and argumentative ability to link the various theoretical and methodological frameworks in computational literary studies.

Exam language

English