Social Networks of Lexical Innovation. Investigating the Social Dynamics of Diffusion of Neologisms on Twitter

Societies continually evolve and speakers use new words to talk about innovative products and practices. While most lexical innovations soon fall into disuse, others spread successfully and become part of the lexicon. In this paper, I conduct a longitudinal study of the spread of 99 English neologis...

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Autor principal:	Quirin Würschinger
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	lexicology lexical innovation sociolinguistics diffusion social media Twitter Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/dba5fc495867482aab63db13abe390a6
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spelling	oai:doaj.org-article:dba5fc495867482aab63db13abe390a62021-11-17T15:06:45ZSocial Networks of Lexical Innovation. Investigating the Social Dynamics of Diffusion of Neologisms on Twitter2624-821210.3389/frai.2021.648583https://doaj.org/article/dba5fc495867482aab63db13abe390a62021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/frai.2021.648583/fullhttps://doaj.org/toc/2624-8212Societies continually evolve and speakers use new words to talk about innovative products and practices. While most lexical innovations soon fall into disuse, others spread successfully and become part of the lexicon. In this paper, I conduct a longitudinal study of the spread of 99 English neologisms on Twitter to study their degrees and pathways of diffusion. Previous work on lexical innovation has almost exclusively relied on usage frequency for investigating the spread of new words. To get a more differentiated picture of diffusion, I use frequency-based measures to study temporal aspects of diffusion and I use network analyses for a more detailed and accurate investigation of the sociolinguistic dynamics of diffusion. The results show that frequency measures manage to capture diffusion with varying success. Frequency counts can serve as an approximate indicator for overall degrees of diffusion, yet they miss important information about the temporal usage profiles of lexical innovations. The results indicate that neologisms with similar total frequency can exhibit significantly different degrees of diffusion. Analysing differences in their temporal dynamics of use with regard to their age, trends in usage intensity, and volatility contributes to a more accurate account of their diffusion. The results obtained from the social network analysis reveal substantial differences in the social pathways of diffusion. Social diffusion significantly correlates with the frequency and temporal usage profiles of neologisms. However, the network visualisations and metrics identify neologisms whose degrees of social diffusion are more limited than suggested by their overall frequency of use. These include, among others, highly volatile neologisms (e.g., poppygate) and political terms (e.g., alt-left), whose use almost exclusively goes back to single communities of closely-connected, like-minded individuals. I argue that the inclusion of temporal and social information is of particular importance for the study of lexical innovation since neologisms exhibit high degrees of temporal volatility and social indexicality. More generally, the present approach demonstrates the potential of social network analysis for sociolinguistic research on linguistic innovation, variation, and change.Quirin WürschingerFrontiers Media S.A.articlelexicologylexical innovationsociolinguisticsdiffusionsocial mediaTwitterElectronic computers. Computer scienceQA75.5-76.95ENFrontiers in Artificial Intelligence, Vol 4 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	lexicology lexical innovation sociolinguistics diffusion social media Twitter Electronic computers. Computer science QA75.5-76.95
spellingShingle	lexicology lexical innovation sociolinguistics diffusion social media Twitter Electronic computers. Computer science QA75.5-76.95 Quirin Würschinger Social Networks of Lexical Innovation. Investigating the Social Dynamics of Diffusion of Neologisms on Twitter
description	Societies continually evolve and speakers use new words to talk about innovative products and practices. While most lexical innovations soon fall into disuse, others spread successfully and become part of the lexicon. In this paper, I conduct a longitudinal study of the spread of 99 English neologisms on Twitter to study their degrees and pathways of diffusion. Previous work on lexical innovation has almost exclusively relied on usage frequency for investigating the spread of new words. To get a more differentiated picture of diffusion, I use frequency-based measures to study temporal aspects of diffusion and I use network analyses for a more detailed and accurate investigation of the sociolinguistic dynamics of diffusion. The results show that frequency measures manage to capture diffusion with varying success. Frequency counts can serve as an approximate indicator for overall degrees of diffusion, yet they miss important information about the temporal usage profiles of lexical innovations. The results indicate that neologisms with similar total frequency can exhibit significantly different degrees of diffusion. Analysing differences in their temporal dynamics of use with regard to their age, trends in usage intensity, and volatility contributes to a more accurate account of their diffusion. The results obtained from the social network analysis reveal substantial differences in the social pathways of diffusion. Social diffusion significantly correlates with the frequency and temporal usage profiles of neologisms. However, the network visualisations and metrics identify neologisms whose degrees of social diffusion are more limited than suggested by their overall frequency of use. These include, among others, highly volatile neologisms (e.g., poppygate) and political terms (e.g., alt-left), whose use almost exclusively goes back to single communities of closely-connected, like-minded individuals. I argue that the inclusion of temporal and social information is of particular importance for the study of lexical innovation since neologisms exhibit high degrees of temporal volatility and social indexicality. More generally, the present approach demonstrates the potential of social network analysis for sociolinguistic research on linguistic innovation, variation, and change.
format	article
author	Quirin Würschinger
author_facet	Quirin Würschinger
author_sort	Quirin Würschinger
title	Social Networks of Lexical Innovation. Investigating the Social Dynamics of Diffusion of Neologisms on Twitter
title_short	Social Networks of Lexical Innovation. Investigating the Social Dynamics of Diffusion of Neologisms on Twitter
title_full	Social Networks of Lexical Innovation. Investigating the Social Dynamics of Diffusion of Neologisms on Twitter
title_fullStr	Social Networks of Lexical Innovation. Investigating the Social Dynamics of Diffusion of Neologisms on Twitter
title_full_unstemmed	Social Networks of Lexical Innovation. Investigating the Social Dynamics of Diffusion of Neologisms on Twitter
title_sort	social networks of lexical innovation. investigating the social dynamics of diffusion of neologisms on twitter
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/dba5fc495867482aab63db13abe390a6
work_keys_str_mv	AT quirinwurschinger socialnetworksoflexicalinnovationinvestigatingthesocialdynamicsofdiffusionofneologismsontwitter
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Social Networks of Lexical Innovation. Investigating the Social Dynamics of Diffusion of Neologisms on Twitter

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