Detecting and categorising lexical innovations in a corpus of tweets - ENS de Lyon - École normale supérieure de Lyon Accéder directement au contenu
Article Dans Une Revue Psychology of Language and Communication Année : 2022

Detecting and categorising lexical innovations in a corpus of tweets

Résumé

In this paper, we present the methodology we have developed for the detection of lexical innovations, implemented here on a corpus of 650 million of French tweets covering a period from 2012 to 2019. Once detected, innovations are categorized as change or buzz according to whether their use has stabilized or dropped over time, and three phases of their dynamics are automatically identified. In order to validate our approach, we further analyse these dynamics by modelling the user network and characterising the speakers using these innovations via network variables. This allows us to propose preliminary observations on the role of individuals in the diffusion process of linguistic innovations which are in line with Milroy & Milroy’s (1997) theories and encourage further investigations.
Fichier principal
Vignette du fichier
10.2478_plc-2022-15.pdf (466.85 Ko) Télécharger le fichier
Origine Publication financée par une institution

Dates et versions

halshs-03719481 , version 1 (23-05-2024)

Identifiants

Citer

Louise Tarrade, Jean-Philippe Magué, Jean-Pierre Chevrot. Detecting and categorising lexical innovations in a corpus of tweets. Psychology of Language and Communication, 2022, 26 (1), pp.313-329. ⟨10.2478/plc-2022-15⟩. ⟨halshs-03719481⟩
82 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More