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Unveiling the Dark Side of Social Media: Developing the First Galician Corpus for Misogyny Detection on Twitter and Mastodon

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http://hdl.handle.net/2183/34240
Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's license is described as Attribution 4.0 International (CC BY 4.0)
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Title
Unveiling the Dark Side of Social Media: Developing the First Galician Corpus for Misogyny Detection on Twitter and Mastodon
Author(s)
Álvarez Crespo, Lucía María
Castro, Laura M.
Date
2023
Abstract
[Abstract] This work aims to develop the first Galician corpus for the detection of misogyny on Twitter and Mastodon. We collect and analyze linguistic data in Galician on these social media platforms, identifying manifestations of misogyny in digital communication. The process involves data collection, text selection, and normalization, followed by thorough cleaning. We apply machine learning techniques to train accurate models for classifying the presence of misogyny. The resulting corpus facilitates analysis and study by research teams interested in misogyny in Galician. This scientific advancement contributes to the understanding and prevention of misogyny in the Galician-speaking community, promoting equality and respect in digital communication in Galician
Keywords
Misoginia
Comunicación digital
Twitter
Mastodon
 
Description
Cursos e Congresos, C-155
Editor version
https://doi.org/10.17979/spudc.000024.14
Rights
Attribution 4.0 International (CC BY 4.0)

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