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.
1° Year
Modules | Credits | TAF | SSD |
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1st foreign language
2nd foreign language
1st foreign literature
2nd foreign literature
One module among the following (philology must be related to one of the chosen languages)
2° Year activated in the A.Y. 2023/2024
Modules | Credits | TAF | SSD |
---|
One activity between the following
Three activities among the following (related to the languages and literatures chosen)
Digital lab
Modules | Credits | TAF | SSD |
---|
1st foreign language
2nd foreign language
1st foreign literature
2nd foreign literature
One module among the following (philology must be related to one of the chosen languages)
Modules | Credits | TAF | SSD |
---|
One activity between the following
Three activities among the following (related to the languages and literatures chosen)
Digital lab
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.
Computational methods for comparative literary studies (2022/2023)
Teaching code
4S010863
Teacher
Credits
6
Language
English
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
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.
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