Beyond the binary: Trans women's video activism on YouTube.
This article aims to analyse aboutness in a corpus of videos posted by Brazilian female transsexual influencers. The analysis is based on Corpus Linguistics, machine learning techniques, and automated lexical mapping techniques, especially Topic Modelling. This technique served as a starting point f...
| Publicado en: | Digital Scholarship in the Humanities Vol. 37; no. 1; pp. 67 - 81 |
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| Formato: | Artículo |
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Oxford University Press / USA
Apr2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=156054098&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 156054098 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 2055768X JEO9 jtl: Digital Scholarship in the Humanities issn: 2055768X maglogo: N pubinfo: dt: Apr2022 vid: 37 iid: 1 pid: 622 pub: Oxford University Press / USA artinfo: ui: 156054098 10.1093/llc/fqab057 ppf: 67 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P size: 451KB tig: atl: Beyond the binary: Trans women's video activism on YouTube. aug: au: Lopes, Rodrigo Esteves de Lima affil: Applied Linguistics, State University of Campinas Institute of Language Studies , Campinas, São Paulo, Brazil su: Trans women Corpora Machine learning Transsexuals sug: subj: Trans women Corpora Machine learning Transsexuals ab: This article aims to analyse aboutness in a corpus of videos posted by Brazilian female transsexual influencers. The analysis is based on Corpus Linguistics, machine learning techniques, and automated lexical mapping techniques, especially Topic Modelling. This technique served as a starting point for establishing four main topics: Relationship and Social Events, Gender, Beauty, and Transition. These topics had their statistically relevant lexis qualitatively analysed by concordance. This study used tools written in R and Python programming languages, made freely available to the community. The results show that the topics are qualitatively and quantitatively consistent, and the approach adopted was fruitful for text analysis. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: © 2019 EADH: The European Association for Digital Humanities. item: Digital Scholarship in the Humanities holder: Oxford University Press / USA dt: @attributes: year: 2022 holdings: @attributes: islocal: N |
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