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brema76/moral_immigration_it
moral_immigration_it is a feature extraction model from brema76. Use it when you need embeddings to search or compare text. It is set up for transformers. The card lists the license as gpl-3.0.
The model aims to assess the moral dimension of Twitter posts in Italian about immigration. Namely, limited to the immigration subject, the model is capable to classify tweets according to the expression of both moral…
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From the Hugging Face model README
The model aims to assess the moral dimension of Twitter posts in Italian about immigration. Namely, limited to the immigration subject, the model is capable to classify tweets according to the expression of both moral dyads:
and <b>concern focuses</b>, i.e, one of
The model was built as part of the European project VALAWAI.
<strong>Citation info and BibTeX entries</strong></br>
<a href="https://www.scitepress.org/Papers/2024/125950/125950.pdf" target="_blank">Fine-Grained Clustering of Social Media: How Moral Triggers Drive Preferences and Consensus</a>
@InProceedings{Bru_Moral2024_2,
author={Brugnoli, Emanuele and Gravino, Pietro and Lo Sardo, Donald Ruggiero and Loreto, Vittorio and Prevedello, Giulio},
title={Fine-Grained Clustering of Social Media: How Moral Triggers Drive Preferences and Consensus},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence (ICAART 2024)},
year={2024},
publisher={SCITEPRESS},
volume={3},
pages={1405--1412},
doi={10.5220/0012595000003636},
isbn={978-989-758-680-4}
}
<a href="https://link.springer.com/chapter/10.1007/978-3-031-58202-8_5" target="_blank">Moral Values in Social Media for Disinformation and Hate Speech Analysis</a>
@InProceedings{Bru_Moral2024,
author={Brugnoli, Emanuele and Gravino, Pietro and Prevedello, Giulio},
editor={Osman, Nardine and Steels, Luc},
title={Moral Values in Social Media for Disinformation and Hate Speech Analysis},
booktitle={Value Engineering in Artificial Intelligence},
year={2024},
publisher={Springer Nature Switzerland},
address={Cham},
pages={67--82},
isbn={978-3-031-58202-8}
}