Norms, affect and evaluation in the reception of literary translations in multilingual online reading communities: Deriving cognitive-evaluative templates from big data

Abstract

This article uses the Digital Opinions on Translated Literature (dioptra-l) corpus to study readers’ perceptions of and responses to translation in a naturalistic setting, focusing on the normative constructs or cognitive evaluative templates they use to conceptualise, evaluate and respond to translations. We answer two main questions: (1) How visible, or salient, is the fact of translation to readers reading a translated literary text, and are there differences in the degree and nature of this visibility for different languages and translation directions? (2) What are the main concepts, and emotional and evaluative parameters that readers use to describe translated literary texts, and are there differences in these concepts and parameters when considered by different translation directionalities and genres? We make use of computational methods, including collocational network analysis, keyword analysis, and sentiment analysis to extract information about the salience of translation, and the networks of emotive and evaluative language that are used around the concept of translation. This forms the basis of our proposals for particular cognitive-evaluative templates.