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:
- 0: care/harm
- 1: fairness/cheating
- 2: loyalty/betrayal
- 3: authority/subversion
- 4: purity/degradation
- 5: no moral
and concern focuses, i.e, one of
- 0: prescriptive (if it highlights a virtue)
- 1: prohibitive (if it blames a misbehaviour)
- 2: no focus
The model was built as part of the European project VALAWAI.
Citation info and BibTeX entries
Fine-Grained Clustering of Social Media: How Moral Triggers Drive Preferences and Consensus
@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}
}
Moral Values in Social Media for Disinformation and Hate Speech Analysis
@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}
}
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