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.

This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)