Characterisation of scientific and popular science discourse in French, Japanese and Russian

We aim to characterise the comparability of corpora, we address this issue in the trilingual context through the distinction of expert and non expert documents. We work separately with corpora composed of documents from the medical domain in three languages (French, Japanese and Russian) which present an important linguistic distance between them. In our approach, documents are characterised in each language by their topic and by a discursive typology positioned at three levels of document analysis: structural, modal and lexical. The document typology is implemented with two learning algorithms (SVMlight and C4.5). Evaluation of results shows that the proposed discursive typology can be transposed from one language to another, as it indeed allows to distinguish the two aimed discourses (science and popular science). However, we observe that performances vary a lot according to languages, algorithms and types of discursive