Research Committee on Digital Comparative Literature (DCL)
In his 2015 article published in Comparative Literature, Matthew Wilkens notes that comparative literature is quite reticent about the growing field of digital humanities. He suggests overcoming this reluctance by testing computer tools for the needs of comparative literature: text mining, network analysis, sociology of literature, clustering, and mapping. Recently, various applications of computational analysis of text corpora and big data (on publication, translation, media resonance, etc.) have been gaining ground in comparative literature. The Stanford Literary Lab, for example, has mapped out the terrain of computerized distant reading, but has yet to test its tools on multilingual corpora.
Admittedly, macro- and micro-analysis (to use Matthew Jockers’s terms) is still struggling to overcome linguistic bias. Computer tools and algorithms have been developed through machine learning using corpora in English and other hyper- or super-central languages. However, some recent attempts, such as the COST Action Distant Reading for European Literary History, are looking for solutions on how to create multilingual corpora as a necessary condition for comparative distant reading. Despite these difficulties, bibliographic and other statistical metadata on individual literary fields, interliterary communities, cultural regions, and the global space open up new perspectives for a comparative study of transnational literary traffic and networks with their spatial nodes, centers and border zones – both in a synchronic and diachronic dimension. In addition, computerized distant reading makes it possible to classify and examine literary forms and genres based on their thematic, stylistic and time- or author-related clustering.
Following the relatively sparse responses to the challenges posed to the humanities by the advent of the Internet and digital media voiced by early birds of our discipline (e.g. Steven Tötösy de Zepetnek’s work since 1995), comparative literature needs to rethink its methods and ask itself whether computer-assisted methods can be a viable alternative or a welcome complement to the methods that characterize the disciplinary tradition. Finally, the recent outbreak of computer-generated texts, translations and other achievements of artificial intelligence once again raises the question of the role of the author and other actors in the literary field. Artificial intelligence is not only a problem or a literary topic that should be studied in a comparative perspective, but can also serve as a tool for comparative literary studies.
The ICLA Research Committee on Digital Comparative Literature (DCL) organizes panels and workshops, publishes papers and special issues to explore the following topics:
- Distant reading techniques and computational literary studies
- Multilingual literary archives and the digitization of texts in different languages and writing systems
- The transformation of the book and reading in the post-digital age; born-digital literature
- Geographic information systems, data visualization and comparative literary studies
- Machine translation, artificial intelligence, language models and comparative literature
Chairperson:
Prof. Simone Rebora, University of Verona (IT)
Co-chair:
Prof. Youngmin Kim, Dongguk University (KR) / Linnaeus University (SE)
Secretary:
Prof. Yina Cao, Sichuan University (CN)
To participate in the activities of the Research Committee, please contact the Chairperson and Co-chair, Prof. Simone Rebora (simone.rebora@univr.it) and Prof. Youngmin Kim (yk4147@daum.net).
For more information on the Research Committee on Digital Comparative Literature, including its members, please click below: