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Translation criticism lacks methods with which to efficiently measure the thematic similarity between a source text and its translation. To address this problem, we focused on a method of automatically assessing such thematic similarity. We proposed a bag-of-words-based LDA topic model to uncover latent topics in a document and used the cosine similarity measure to compute the similarity between topics. We hypothesized that the similarity between the topics of an original text and its translation reflects the level of thematic similarity between them. To test the hypothesis, we applied the proposed LDA-cosine method to a novel by F. M. Dostoevsky, "The Brothers Karamazov" (1880), and its English translation by Constance Garnett (1912). Two texts were assumed to be thematically similar to a high degree. We used the results of the method s application to test this assumption.

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Natali Karlova-Bourbonus is a Ph.D. student in the Department of Applied Linguistics at the University of Giessen and writes her dissertation on automatic detection of contradictions in texts. She received her B.A. in German Literature from the University of Constance and M.A. in Computational Linguistics from the Technical University of Darmstadt.

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