Detecting and categorising lexical innovations in a corpus of tweets

Q2 Arts and Humanities Psychology of Language and Communication Pub Date : 2022-01-01 DOI:10.2478/plc-2022-15
Louis Tarrade, Jean-Philippe Magué, Jean-Pierre Chevrot
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Abstract

Abstract 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.
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推文语料库中词汇创新的检测和分类
摘要在本文中,我们介绍了我们为检测词汇创新而开发的方法,该方法在2012年至2019年期间的6.5亿条法语推文语料库中实现。一旦被检测到,创新就会根据其使用是否随着时间的推移而稳定或下降,被归类为变化或嗡嗡声,并自动识别其动态的三个阶段。为了验证我们的方法,我们通过对用户网络进行建模,并通过网络变量使用这些创新来表征演讲者,从而进一步分析这些动态。这使我们能够对个人在语言创新传播过程中的作用提出初步的观察,这符合Milroy和Milroy(1997)的理论,并鼓励进一步的研究。
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来源期刊
Psychology of Language and Communication
Psychology of Language and Communication Arts and Humanities-Language and Linguistics
CiteScore
0.80
自引率
0.00%
发文量
11
审稿时长
14 weeks
期刊最新文献
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