{"title":"Emergent Twitter publics through political scandal","authors":"C. Rathnayake, Angela Smith, Michael Higgins","doi":"10.1075/jlp.22028.rat","DOIUrl":null,"url":null,"abstract":"\n This study examines how emergent Twitter publics are organised and engage with political scandal and\n personalisation during Covid-19 in the UK. The analysis is centred on a series of media events around Chief Adviser to the then-UK\n Prime Minister, running from May 2020 to May 2021. The samples comprises original tweets that contain key hashtags, amounting to\n 38,326 items. These are subject to topic model analysis to identify semantic fields, before using critical discourse analysis. We\n find hashtags help constitute emergent Twitter publics, and that tweets follow conversational patterns and conspire in tactics of\n intertextuality. Dissention to government conduct engages resourcefully with the affordances of Twitter: constituting publics,\n shaping discourse, and articulating with parallel discussions on political performance. Further, a computational approach can\n systematise the identification of domains of discourse and relevant lexical sets, providing an evidence-based understanding of\n even novel and emergent political discourses in online discussion.","PeriodicalId":51676,"journal":{"name":"Journal of Language and Politics","volume":" ","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Language and Politics","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1075/jlp.22028.rat","RegionNum":3,"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: 0
Abstract
This study examines how emergent Twitter publics are organised and engage with political scandal and
personalisation during Covid-19 in the UK. The analysis is centred on a series of media events around Chief Adviser to the then-UK
Prime Minister, running from May 2020 to May 2021. The samples comprises original tweets that contain key hashtags, amounting to
38,326 items. These are subject to topic model analysis to identify semantic fields, before using critical discourse analysis. We
find hashtags help constitute emergent Twitter publics, and that tweets follow conversational patterns and conspire in tactics of
intertextuality. Dissention to government conduct engages resourcefully with the affordances of Twitter: constituting publics,
shaping discourse, and articulating with parallel discussions on political performance. Further, a computational approach can
systematise the identification of domains of discourse and relevant lexical sets, providing an evidence-based understanding of
even novel and emergent political discourses in online discussion.