Distant, Deep, Thick Reading across Languages: Building towards Inclusive Digital Epistemologies of Text

While distant reading in one language is relatively straightforward, computation across languages poses epistemo-semiotic challenges. The fundamental problem here is how to cut across many texts in different languages in a way that would yield rich data and narratives about translated texts as socio-cultural artefacts. What cross-linguistic computational text analysis has to overcome, among other things, are technological conformism, linguistic colonialism, and reductive interpretations akin to the lack of ‘thick descriptions’ observed in cultural anthropology (Geertz 1973). In this presentation, the team of the DRaL (Distant Reading across Languages) project will discuss the techniques of modelling translatorial choices with word frequencies and repetition strings as patterns of dynamic behaviour. The context-aware computing is a major concern that drives the project towards building a visually rich narrative as a form of distant/deep/thick reading which would be inclusive of minority languages and their role in the making of global literature.