paper-with-me

홈 › Papers

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

2026-02-13 · Maria Ryskina, Matthew R. Gormley, Kyle Mahowald, David R. Mortensen, Taylor Berg-Kirkpatrick, Vivek Kulkarni arxiv

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 conversational context: language use in newspapers is subject to very different constraints than language use on social media. Prior distributional semantic work on English word emergence (neology) identified two factors correlated with creation of new words by analyzing a corpus consisting primarily of historical published texts (Ryskina et al., 2020, arXiv:2001.07740). Extending this methodology to contextual embeddings in addition to static ones and applying it to a new corpus of Twitter posts, we show that the same findings hold for both domains, though the topic popularity growth factor may contribute less to neology on Twitter than in published writing. We hypothesize that this difference can be explained by the two domains favouring different neologism formation mechanisms.

📄 PDF Abstract BibTeX arXiv:2602.13123

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Character Based Pattern Mining for Neology Detection

2017-09-01 · WS 2017 9 · Ga{\"e}l Lejeune, Emmanuel Cartier

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…

General Classification

Technical Term Extraction Using Measures of Neology

2015-07-01 · WS 2015 7 · Christopher Norman, Akiko Aizawa
Term Extraction

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

2014-08-01 · WS 2014 8 · Jes{\'u}s Torres-del-Rey, Nava Maroto

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

2026-05-20 · Nina Hosseini-Kivanani arxiv

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…

TTSDS -- Text-to-Speech Distribution Score

2024-07-17 · Christoph Minixhofer, Ondřej Klejch, Peter Bell

Many recently published Text-to-Speech (TTS) systems produce audio close to real speech. However, TTS evaluation needs to be revisited to make sense of the results obtained with the new architectures, approaches and data…

text-to-speechText to Speech