{"title":"Linguistic Accommodation in Teenagers’ Social Media Writing: Convergence Patterns in Mixed-gender Conversations","authors":"Lisa Hilte, R. Vandekerckhove, Walter Daelemans","doi":"10.1080/09296174.2020.1807853","DOIUrl":null,"url":null,"abstract":"ABSTRACT The present study analyzes the phenomenon of linguistic accommodation, i.e. the adaptation of one’s language use to that of one’s conversation partner. In a large corpus of private social media messages, we compare Flemish teenagers’ writing in two conversational settings: same-gender (including only boys or only girls) and mixed-gender conversations (including at least one girl and one boy). We examine whether boys adopt a more ‘female’ and girls a more ‘male’ writing style in mixed-gender talks, i.e. whether teenagers converge towards their conversation partner with respect to gendered writing. The analyses focus on two sets of prototypical markers of informal online writing, for which a clear gender divide has been attested in previous research: expressive typographic markers (e.g., emoticons), which can be considered more ‘female’ features, and ‘oral’, speech-like markers (e.g., regional language features), which are generally more popular among boys. Using generalized linear-mixed models, we examine the frequency of these features in boys’ and girls’ writing in same- versus mixed-gender conversations. Patterns of convergence emerge from the data: they reveal that girls and boys adopt a more similar style in mixed-gender talks. Strikingly, the convergence is asymmetrical and only significant for a particular group of online language features.","PeriodicalId":45514,"journal":{"name":"Journal of Quantitative Linguistics","volume":"29 1","pages":"241 - 268"},"PeriodicalIF":0.7000,"publicationDate":"2020-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09296174.2020.1807853","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Quantitative Linguistics","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1080/09296174.2020.1807853","RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"LANGUAGE & LINGUISTICS","Score":null,"Total":0}
引用次数: 14
Abstract
ABSTRACT The present study analyzes the phenomenon of linguistic accommodation, i.e. the adaptation of one’s language use to that of one’s conversation partner. In a large corpus of private social media messages, we compare Flemish teenagers’ writing in two conversational settings: same-gender (including only boys or only girls) and mixed-gender conversations (including at least one girl and one boy). We examine whether boys adopt a more ‘female’ and girls a more ‘male’ writing style in mixed-gender talks, i.e. whether teenagers converge towards their conversation partner with respect to gendered writing. The analyses focus on two sets of prototypical markers of informal online writing, for which a clear gender divide has been attested in previous research: expressive typographic markers (e.g., emoticons), which can be considered more ‘female’ features, and ‘oral’, speech-like markers (e.g., regional language features), which are generally more popular among boys. Using generalized linear-mixed models, we examine the frequency of these features in boys’ and girls’ writing in same- versus mixed-gender conversations. Patterns of convergence emerge from the data: they reveal that girls and boys adopt a more similar style in mixed-gender talks. Strikingly, the convergence is asymmetrical and only significant for a particular group of online language features.
期刊介绍:
The Journal of Quantitative Linguistics is an international forum for the publication and discussion of research on the quantitative characteristics of language and text in an exact mathematical form. This approach, which is of growing interest, opens up important and exciting theoretical perspectives, as well as solutions for a wide range of practical problems such as machine learning or statistical parsing, by introducing into linguistics the methods and models of advanced scientific disciplines such as the natural sciences, economics, and psychology.