The paper explores the importance of closer interaction between data science and evolutionary linguistics, pointing to the potential benefits for both disciplines. In the context of big data, the microblogging social networking service – Twitter – can be treated as a source of empirical input for analyses in the field of language evolution. In an attempt to utilize this kind of disciplinary interplay, I propose a model, which constitutes an adaptation of the Iterated Learning framework, for investigating the glossogenetic evolution of sublanguages.
