The translator's visibility: Detecting translatorial fingerprints in contemporaneous parallel translations.

•We examine the stylistic fingerprint of two sets of literary translators.•We use machine learning techniques such as SVMs, Nave Bayes and Simple Logistic Regression which are relatively novel approaches to the task.•We find that common words and bigrams are strong discriminators of translators style based on two authors, who original wrote in Russian and Norwegian and were translated to English.•We find that translators style remains discriminable across non-parallel translations of the same author.•We also find that textual metrics such as common verb frequencies are strong indicators of translators style in both cases, in line with prior studies in the literature.