# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "text" in publications use:' type: software license: GPL-3.0-only title: 'text: Analyses of Text using Transformers Models from HuggingFace, Natural Language Processing and Machine Learning' version: 1.3.0 doi: 10.1037/met0000542 identifiers: - type: doi value: 10.32614/CRAN.package.text - type: url value: https://github.com/OscarKjell/text/ abstract: Link R with Transformers from Hugging Face to transform text variables to word embeddings; where the word embeddings are used to statistically test the mean difference between set of texts, compute semantic similarity scores between texts, predict numerical variables, and visual statistically significant words according to various dimensions etc. For more information see . authors: - family-names: Kjell given-names: Oscar email: oscar.kjell@psy.lu.se orcid: https://orcid.org/0000-0002-2728-6278 - family-names: Giorgi given-names: Salvatore orcid: https://orcid.org/0000-0001-7381-6295 - family-names: Schwartz given-names: Andrew orcid: https://orcid.org/0000-0002-6383-3339 preferred-citation: type: article title: 'The text-package: An R-package for Analyzing and Visualizing Human Language Using Natural Language Processing and Deep Learning' authors: - family-names: Kjell given-names: Oscar email: oscar.kjell@psy.lu.se orcid: https://orcid.org/0000-0002-2728-6278 - family-names: Giorgi given-names: Salvatore orcid: https://orcid.org/0000-0001-7381-6295 - family-names: Schwartz given-names: H. Andrew journal: Psychological Methods doi: 10.1037/met0000542 year: '2023' url: https://osf.io/preprints/psyarxiv/293kt/ repository: https://CRAN.R-project.org/package=text repository-code: https://github.com/OscarKjell/text/issues/ url: https://r-text.org/ date-released: '2024-12-05' contact: - family-names: Kjell given-names: Oscar email: oscar.kjell@psy.lu.se orcid: https://orcid.org/0000-0002-2728-6278