Informatica applicata al testo letterario - 2017-2018 - Laurea magistrale

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Italiano
Prerequisiti: 

Conoscenza dei problemi di base dell'informatica per le scienze umanistiche e competenze di teoria e metodologia degli studi letterari

Obiettivi: 

L'insegnamento di Informatica applicata al testo letterario per la laurea magistrale mira a fornire una preparazione approfondita nel settore dell'applicazione delle nuove tecnologie digitali allo studio e all'analisi del testo letterario, una conoscenza avanzata delle tecniche e delle problematiche legate alla creazione e alla diffusione dei documenti elettronici e alla creazione e gestione di biblioteche digitali, e delle nuove tipologie di testualità sviluppatesi nell'ambito della comunicazione digitale.

 

 

Programma: 

Titolo del corso: Computational methods for literary text representation and analysis

The course will give the theoretical foundations and the operational competences required to create and analyze digital textual resources. I will cover the following issues:

  • Formal and computational models of Textuality
  • Advanced methods for scholarly text encoding and representation: XML and Text Encoding Initiative markup language
  • Models and framework for scholarly editing and publishing of digital text collections
  • The classical methods of text analysis: concordances, text retrieval and frequentist statistical analysis
  • Distant reading and cultural analytics theoretical and methodological rationales
  • Text mining textual corpora: cluster analysis, topic modelling and word2vec
Testi adottati: 

L. Burnard. 2014. What is the Text Encoding Initiative? How to add intelligent markup to digital resources. Marseille : OpenEdition Press. Web. http://books.openedition.org/oep/426

M. Jockers. 2013. Macroanalysis: Digital Methods and Literary History. University of Illinois Press

F. Ciotti. 2015. Sul distant reading: una visione critica. Semicerchio, LIII(2)

T. Underwood. 2017. A Genealogy of Distant Reading. Digital Humanities Quarterly 11(2). Web: http://www.digitalhumanities.org/dhq/vol/11/2/000317/000317.html

Inglese
Prerequisites: 

Basic knwoledge of Digital Humanities, Literary Theory and Literary Criticism issues

Aims: 

The course aims to provide a thorough knowledge in the application of digital methods and tools for the study and analysis of literary texts, an advanced knowledge of the techniques and issues related to the creation and the dissemination of electronic documents and the creation and management of digital libraries, and new types of textuality developed in the context of digital communication.

Programme: 

Title: Computational methods for literary text representation and analysis

The course will give the theoretical foundations and the operational competences required to create and analyze digital textual resources. I will cover the following issues:

  • Formal and computational models of Textuality
  • Advanced methods for scholarly text encoding and representation: XML and Text Encoding Initiative markup language
  • Models and framework for scholarly editing and publishing of digital text collections
  • The classical methods of text analysis: concordances, text retrieval and frequentist statistical analysis
  • Distant reading and cultural analytics theoretical and methodological rationales
  • Text mining textual corpora: cluster analysis, topic modelling and word2vec
Texts adopted: 

L. Burnard. 2014. What is the Text Encoding Initiative? How to add intelligent markup to digital resources. Marseille : OpenEdition Press. Web. http://books.openedition.org/oep/426

M. Jockers. 2013. Macroanalysis: Digital Methods and Literary History. University of Illinois Press

F. Ciotti. 2015. Sul distant reading: una visione critica. Semicerchio, LIII(2)

T. Underwood. 2017. A Genealogy of Distant Reading. Digital Humanities Quarterly 11(2). Web: http://www.digitalhumanities.org/dhq/vol/11/2/000317/000317.html

Modalità di erogazione: 
Tradizionale
Frequenza: 
Consigliata
Valutazione: 
Prova orale
Valutazione progetto
Anno Accademico: 
2017-2018
Docente: 
Ore: 
30
CFU: 
6