DIGITAL HUMANITIES 3: DIGITAL TEXT ANALYSIS

Academic year
2020/2021 Syllabus of previous years
Official course title
DIGITAL HUMANITIES 3: DIGITAL TEXT ANALYSIS
Course code
ECC033 (AF:345554 AR:181980)
Modality
ECTS credits
6
Degree level
Istituto d`eccellenza
Educational sector code
SECS-S/01
Period
1st Semester
Course year
1
Moodle
Go to Moodle page
The course allows to acquire theoretical and practical knowledge on the main techniques in digital text analysis and natural language processing.
Theoretical and practical knowledge on the main techniques in digital text analysis and computational linguistics.
DIGITAL HUMANITIES 1
DIGITAL HUMANITIES 2
The course offers an introduction to automatic text analysis from the Digital Humanities perspective. It is structured in three parts. The first is theoretical and introduces the student to computational linguistics with particular attention to distributional semantics and topic modelling. The second is practical and focuses on text analysis tools, including the Python programming language and the spaCy and Stanza libraries. The third part is dedicated to the digital analysis of literary texts, with the presentation of various case studies.
The references will be given during the lessons

Recommended readings:
- Dan Jurafsky and James H. Martin, "Speech and Language Processing", (3rd ed. draft), https://web.stanford.edu/~jurafsky/slp3/
- Al Sweigart, "Automate the Boring Stuff with Python Programming", https://automatetheboringstuff.com
- Stanford Literary Lab, https://litlab.stanford.edu/pamphlets/
Presentation of a digital text analysis project developed by the student.
Frontal lessons and classroom exercises.
oral
This programme is provisional and there could still be changes in its contents.
Last update of the programme: 10/08/2020