In this presentation Prof. Dr. Haidee Kotze considers particularly corpus-assisted and computational methods, which have mostly made use of the affordances of large quantities of user-generated book reviews from digital reading and reviewing communities like Goodreads. Such platforms offer unparalleled opportunities for investigating the reception of translation in a naturalistic setting, and on both large and small scale. She contrasts two ways of analysing such data – computational or distant-reading analyses and close-reading narrative analysis – using the DIOPTRA-L (Digital Opinions on Translated Literature) database. DIOPTRA-L contains Goodreads reviews of approximately 100 contemporary literary texts that have been translated from and into Afrikaans, Dutch, English, French, German, Italian, Portuguese and Spanish. The corpus currently contains around 280 000 reviews and 33 million running words (see Kotze et al. 2021). She uses this data to illustrate how computational and close-reading methods can be used in complementary ways to explore how factors like genre and translation language pair influence the cognitive and emotional ‘templates’ that readers use to evaluate and respond to translated literary texts, and how readers’ personal backgrounds intersect with these general patterns. 

Haidee Kotze is professor and chair of translation studies at Utrecht University, and editor-in-chief of the journal Target. Her research explores the complexities of cognitive, linguistic, social, institutional and ideological aspects of different forms of translation and language contact in multilingual settings.