Technical Term Extraction Using Measures of Neology

Character Based Pattern Mining for Neology Detection

Detecting neologisms is essential in real-time natural language processing applications. Not only can it enable to follow the lexical evolution of languages, but it is also essential for updating linguistic resources and…

From sunblock to softblock: Analyzing the correlates of neology in published writing and on social media

Living languages are shaped by a host of conflicting internal and external evolutionary pressures. While some of these pressures are universal across languages and cultures, others differ depending on the social and conv…

Building the Interface between Experts and Linguists in the Detection and characterisation of Neology in the Field of Neurosciences

Do LLMs Know What Luxembourgish Borrows? Probing Lexical Neology in Low-Resource Multilingual Models

Large language models (LLMs) are increasingly used for writing assistance in small contact languages, yet it is unclear whether they respect community norms around lexical borrowing and neology. We introduce LexNeo-Bench…

A statistical significance testing approach for measuring term burstiness with applications to domain-specific terminology extraction

A term in a corpus is said to be ``bursty'' (or overdispersed) when its occurrences are concentrated in few out of many documents. In this paper, we propose Residual Inverse Collection Frequency (RICF), a statistical sig…