In this article, we explore several computational methods for studying retranslation using twenty-two translations of Kafka’s (1915) Die Verwandlung ‘The metamorphosis’ into English and Spanish as a case study. By comparing multiple translations across two languages, we seek to address the relative lack of crosslinguistic studies in this area. In addition, by adopting a computational approach, we hope to demonstrate that basic statistical methods can enhance the small but promising set of recent studies on how retranslation reveals features in the original text that challenge translators or encourage variation in translations. Much of the scholarship on the topic of retranslation, as well as on translation variation more generally, has followed a different path, subordinating text to context and emphasizing the individual psychological and sociocultural factors driving translator decision-making. On the individual side, for example, Venuti (2003) describes retranslation as a self-conscious act of differentiation, Pym (1998) frames it in terms of a challenge, and Koskinen and Paloposki (2015) adopt Bloom’s (1973) notion of the ‘anxiety of influence’ to elucidate the relationship of retranslations to the work of the original translator. A distinct but related approach characterizes work in both qualitative and quantitative Translation Studies that seeks to identify a particular translator’s style or identify her ‘thumbprint’ in the text of a translation (e.g., Baker 2000; Rybicki 2012; Wang and Li 2012). More socioculturally oriented studies, in contrast, seek to address the broader forces, of which there are many, that shape differences in translation. Jones (2020) studies a corpus of translations of Thucydides to identify shifts in attitudes toward history writing. Brownlie (2006) shows how translations of Zola’s (1880) Nana reflect, albeit with some notable exceptions, the norms and ideologies of the time in which they appeared. And in her pioneering book-length study of the topic, Deane-Cox (2014) elucidates an assortment of genre-, market-, and institution-based drivers of variation.

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