Assessing the Pragmatic Competence of LLMs Regarding Novel Discourse Markers in Digital Communication
Proceedings of the Workshop Neology and Large Language Models
Abstract
The English language is changing faster than before, partly due to the influence of the Internet. Digital language includes a large number of discourse markers (DMs), many of which can be considered innovative. Acronymization, pragmatic specialisation, and compensatory lexical innovation are the most common lexical processes that can be witnessed in the DMs used in computer-mediated communication (CMC). The following novel DMs were identified in recent Twitter chats: lol, tbh, omg, meh, and idk. These DMs perform several functions, such as showing emotions, signalling uncertainty, hesitation, or mitigation. Interpreting these functions may not be an easy or obvious task for AI. The primary aim of the study is to evaluate the pragmatic competence of an LLM, Gemini 3 Pro, regarding the interpretation of these novel DMs. A mixed-method research process was employed: LLM-generated outputs were compared with the findings of the relevant literature, quantitative corpus analysis, and our qualitative human interpretation to assess the model’s analytical usefulness. Gemini 3 Pro was found to show a high level of pragmatic competence in terms of interpreting the functions of DMs, but sometimes tended to overgeneralise, or failed to understand the tone of the text and the intention of the speaker to use a DM.