A Predictive Approach to Semantic Change Modelling

Abstract : Although it is well known that word meaning evolves over time, the cause and the pace of change is still largely unknown. In this context, computational modelling can shed new light on the problem by considering at the same time a large number of variables that are supposed to interact in the process. This field has already given birth to a large number of publications ranging from early work involving statistical and mathematical formalism (Bailey, 1973 ; Kroch, 1989) to more recent work involving robotics and large-scale simulations (Steels, 2011). We consider that semantic change includes all kinds of change in the meanings of lexical items happening over the years. In this work, we address the question of semantic change from a computational point of view. Our aim is to capture the systemic change of words meanings in an empirical model that is also predictive, contrary to most previous approaches that try to model and account for past data.
Keywords : language evolution
Complete list of metadatas

Cited literature [8 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-02265227
Contributor : Thierry Poibeau <>
Submitted on : Thursday, August 8, 2019 - 7:37:10 PM
Last modification on : Sunday, August 11, 2019 - 1:08:32 AM

File

ling_change_amine_dh2019.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02265227, version 1

Citation

Mohamed Boukhaled, Benjamin Fagard, Thierry Poibeau. A Predictive Approach to Semantic Change Modelling. Digital Humanities, Jul 2019, Utrecht, Netherlands. ⟨hal-02265227⟩

Share

Metrics

Record views

18

Files downloads

3