At the intersection of computational modelling, data analysis and statistics, data science is gradually developing across all scientific domains, and the humanities and social sciences are no exception. Especially in these latter fields, data science rests on an epistemology and a range of techniques which strengths and weaknesses differ from those of longer-established approaches (Kitchin, 2014; Leonelli, 2010). This opens the way to fruitful collaborations between scholars of complementary expertise, and can offer fresh perspectives on old and complex issues. As an illustration of what precedes, linguistics has seen a steady increase in quantitative approaches in recent years, and large datasets [...]