Macchine per leggere: promuovere la lettura con il distant reading
DOI:
https://doi.org/10.54103/2037-2426/19557Keywords:
Reading Strategies, Reading Promotion, Text Analysis, Distant Reading, Classics of Italian LiteratureAbstract
References
Bianchi, Federico, Debora Nozza e Dirk Hovy. “FEEL-IT: Emotion and Sentiment Classification for the Italian Language”. Proceedings of the Eleventh Workshop on Computa-tional Approaches to Subjectivity, Sentiment and Social Media Analysis, Association for Com-putational Linguistics, pp. 76-83.
Ciotti, Fabio. “What’s in a Topic Model? Critica teorica di un metodo computazionale per l’analisi del testo”. Testo e Senso, n. 18, 2017.
Croxall, Brian, e Diane Jakacki (a cura di). Debates in Digital Humanities Pedagogy. U of Minnesota P, forthcoming.
D’Annunzio, Gabriele. Il Piacere. A cura di Angelo Piero Cappello, BUR Rizzoli, 2021.
Dascalu, Mihai, et al. “ReaderBench, an Environment for Analyzing Text Complexity and Reading Strategies”. Artificial Intelligence in Education. AIED 2013. Lecture Notes in Com-puter Science, a cura di H. Chad Lane, Kalina Yacef, Jack Mostow e Philip Pavlik, Springer, 2013, pp. 379-88.
Firth, John Rupert. Papers in Linguistics 1934–1951. Oxford UP, 1957.
Gavin, Michael. Literary Mathematics: Quantitative Theory for Textual Studies. Stanford UP, 2022.
Giusti, Simone. Didattica della letteratura 2.0. 2015. Carocci, 2020.
Hirsch, Brett D,.editor. Digital Humanities Pedagogy: Practices, Principles and Politics. Open Book Publishers, 2012.
Hogan, Patrick Colm, et al. (a cura di). The Routledge Companion to Literature and Emotion. Routledge, 2022.
Iannella, Alessandro. “‘Ok Google, vorrei parlare con la poetessa Saffo’: Intelligenza Artificiale, assistenti virtuali e didattica della letteratura”. Thamyris, nova series: Revista de Didáctica de Cultura Clásica, Griego y Latín, vol. 10, 2019, pp. 81-104.
Jannidis, Fotis, et al. “Comparison of Methods for the Identification of Main Charac-ters in German Novels”. Digital Humanities 2016: Conference Abstracts, a cura di Maciej Eder, Jan Rybicki, Jagiellonian University & Pedagogical University, 2016, pp. 578-82.
Jasonov Milán. “A Network Map of The Witcher”. Nightingale. Journal of the Data Visuali-zation Society, 2021.
Jockers, Matthew L. Macroanalysis: Digital Methods and Literary History. U of Illinois P, 2013.
John, Markus, et al. “A Visual Approach for the Comparative Analysis of Character Networks in Narrative Texts”. 2019 IEEE Pacific Visualization Symposium, IEEE, 2019, pp. 247-56.
Kim, Hoyeol. “Sentiment Analysis: Limits and Progress of the Syuzhet Package and Its Lexicons”. Digital Humanities Quarterly, vol. 16, n. 2, 2022.
Lana, Maurizio. Introduzione all’information literacy: storia, modelli, pratiche. Editrice Biblio-grafica, 2020.
Landow, George P. Hypertext 2.0: The Convergence of Contemporary Critical Theory and Technology. Johns Hopkins UP, 1997.
Liu, Bing. Sentiment analysis: mining opinions, sentiments, and emotions. Cambridge UP, 2015.
Macaya, María, e Manuel Perea. “Does Bold Emphasis Facilitate the Process of Visual-Word Recognition?”. The Spanish Journal of Psychology, vol. 17, 2014.
Magherini, Simone. “Strumenti informatici per la letteratura italiana”. Didattica della lette-ratura italiana. Riflessioni e proposte educative, a cura di Gino Ruozzi, Gino Tellini, Le Monnier Università-Mondadori Education, 2020, pp. 173-84.
Moretti, Franco. A una certa distanza: leggere i testi letterari nel nuovo millennio. Carocci, 2020.
—. “Conjectures on World Literature”. The New Left Review, II, 1, 2000.
—. “Network Theory, Plot Analysis”. Stanford Literary Lab Pamhplets, n. 2, 2011.
Plecháč, Petr, et al. (a cura di). Tackling the Toolkit. Plotting Poetry through Computational Liter-ary Studies. Institute of Czech Literature of the Czech Academy of Sciences, 2021.
Reagan, Andrew J., et al. “The Emotional Arcs of Stories are Dominated by Six Basic Shapes”. EPJ Data Science, vol. 5, 2016.
Retaegui, Eliseo, et al. “Can Text Mining Support Reading Comprehension?”. Methodolo-gies and Intelligent Systems for Technology Enhanced Learning, 9th International Conference, Ros-sella Gennari, Pierpaolo Vittorini, Fernando De la Prieta, et al. (a cura di), Springer, 2020, pp. 37-44.
Rhody, Lisa. “Topic Modeling and Figurative Language”. Journal of Digital Humanities, vol. 2, no. 1.
Riva, Francesca. Insegnare letteratura nell’era digitale. Edizioni ETS, 2017.
Roncaglia, Gino. L’età della frammentazione: cultura del libro e scuola digitale. Laterza, 2020.
Sanocki, Thomas, e Mary C. Dyson. “Letter Processing and Font Information During Reading: Beyond Distinctiveness, where Vision Meets Design”. Atten Percept Psycho-phys, vol. 74, 2012, pp. 132-45.
Sarti, Luca. “Narrare i classici nell’era digitale. Dai tweet alle emoji: il caso di Pinocchio”. Una/Κοινῇ, n. 1, 2021, pp. 152-98.
Schreibman, Susan, Raymond George Siemens e John Unsworth (a cura di). A Compan-ion to Digital Humanities. Blackwell Publishing, 2004.
—. A New Companion to Digital Humanities. Wiley-Blackwell, 2016.
Sinclair, Stéfan, e Geoffrey Rockwell. Hermeneutica: Computer-Assisted Interpretation in the Humanities. MIT P, 2016.
Smeets, Roel. Character Constellations. Representations of Social Groups in Present-Day Dutch Liter-ary Fiction. Leuven UP, 2021.
Swafford, Annie. “Problems with the Syuzhet Package”. Anglophile in Academia: Annie Swafford’s Blog.
Underwood, Ted. Distant horizons: Digital Evidence and Literary Change. The U of Chicago P, 2019.
Valitutti, Alessandro, e Cecilia Dalla Torre. “‘Io non ho paura’: Sentiment analysis nell’analisi di testi narrativi”. Proceedings of Didamatica-21, AICA, 2021, pp. 166-69.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Except where otherwise noted, the content of this site is licensed under a Creative Commons Attribution 4.0 Unported License.