The purpose of this article and the journal issue as a whole is to present modern areas of research in computational linguistics and linguistic complexology, as well as to define a solid rationale for the new interdisciplinary field, i.e.

The dramatic expansion of modern linguistic research and enhanced accuracy of linguistic analysis have become a reality due to the ability of artificial neural networks not only to learn and adapt, but also carry out automate linguistic analysis, select, modify and compare texts of various types and genres. By bringing these perspectives together, we contribute to a critical assessment of how linguistic research is motivated by both epistemic and non-epistemic goals. Due to its normative dimension, the notion of complexity has also served as a vehicle for advancing ideological agendas, such as characterizing speakers as more or less advanced based on perceived properties of their languages. By contrast, the claim about the universality of syntactic recursion was primarily informed by theoretical considerations. Thus, Menzerath’s law about complexity trade-offs was inspired by bottom-up empirical observations. In this Research Topic, we investigate the motivations driving the research on linguistic complexity. In consequence, debates on linguistic complexity shape our perception of human nature and variation among human populations. nurture in human cognition and culture, or the distinction between message and noise in information theory. Discussions concerning complexity have implications that go far beyond linguistics in the narrow sense, including e.g.

These debates focus on such issues as the universality of syntactic recursion, the exceptional simplicity of creole languages, complexity trade-offs between structural levels, as well as sociolinguistic correlates of complexity profiles. The question whether all languages are similarly complex is at the centre of some of the most heated debates within linguistics.

Sociolinguistics trudgill pdf