EmoHopeSpeech: An Annotated Dataset of Emotions and Hope Speech in English and Arabic

Abstract

This research introduces a bilingual dataset comprising 27,456 entries for Arabic and 10,036 entries for English, annotated for emotions and hope speech, addressing the scarcity of multi-emotion datasets. The dataset provides comprehensive annotations capturing emotion intensity, complexity, and causes, alongside detailed classifications and subcategories for hope speech. To ensure annotation reliability, Fleiss’ Kappa was employed, revealing 0.75–0.85 agreement among annotators for both Arabic and English. The evaluation metrics (microF1-Score = 0.67) obtained from the baseline AraBERT model validate the quality of the data annotations.