LEIA: Linguistic Embeddings for the Identification of Affect

The wealth of text data generated by social media has enabled new kinds of analysis of emotions with language models. These models are often trained on small and costly datasets of text annotations produced by readers who guess the emotions expressed by others in social media posts. This affects the...

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Detalles Bibliográficos
Autores principales: Aroyehun, Segun Taofeek, Malik, Lukas, Metzler, Hannah, Haimerl, Nikolas, Di Natale, Anna, Garcia, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Regular Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10654159/
https://www.ncbi.nlm.nih.gov/pubmed/38020476
http://dx.doi.org/10.1140/epjds/s13688-023-00427-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10654159/
https://www.ncbi.nlm.nih.gov/pubmed/38020476
http://dx.doi.org/10.1140/epjds/s13688-023-00427-0

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