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11 mai 2021
- doi: 10.4000/books.aaccademia.7129
- eisbn: 9791280136329
https://creativecommons.org/licenses/by-nc-nd/4.0/ , info:eu-repo/semantics/openAccess
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EVALITA COVID-19 Infodemic linguistica computazionale Automatic Misogyny Identification Misogyny on Twitter Posts AlBERTo Convolutional Neural Network BERT Model Hate Speech Detection Multimodal Meme Detection MEME management Language Game ``La Ghigliottina'' Language & Linguistics LAN000000 CBXSujets proches
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María S. Espinosa et al., « DeepReading @ SardiStance: Combining Textual, Social and Emotional Features », Accademia University Press, ID : 10.4000/books.aaccademia.7129
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Résumé
In this paper we describe our participation to the SardiStance shared task held at EVALITA 2020. We developed a set of classifiers that combined text features, such as the best performing systems based on large pre-trained language models, together with user profile features, such as psychological traits and social media user interactions. The classification algorithms chosen for our models were various monolingual and multilingual Transformer models for text only classification, and XGBoost for the non-textual features. The combination of the textual and contextual models was performed by a weighted voting ensemble learning system. Our approach obtained the best score for Task B, on Contextual Stance Detection.