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

Wajdi Zaghoauni; Md Rafiul Biswas

doi:10.26615/978-954-452-098-4-162

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

Wajdi Zaghoauni
, Md Rafiul Biswas

HBKU College of Science and Engineering

Northwestern University in Qatar

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

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.

Original language	English
Title of host publication	Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era, RANLP 2025
Editors	Galia Angelova, Maria Kunilovskaya, Marie Escribe, Ruslan Mitkov
Publisher	Incoma Ltd
Pages	1406-1412
Number of pages	7
ISBN (Electronic)	9789544520984
DOIs	https://doi.org/10.26615/978-954-452-098-4-162
Publication status	Published - 10 Sept 2025
Event	15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era, RANLP 2025 - Varna, Bulgaria Duration: 8 Sept 2025 → 10 Sept 2025

Publication series

Name	International Conference Recent Advances in Natural Language Processing, RANLP
ISSN (Print)	1313-8502

Conference

Conference	15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era, RANLP 2025
Country/Territory	Bulgaria
City	Varna
Period	8/09/25 → 10/09/25

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10.26615/978-954-452-098-4-162

Cite this

Zaghoauni, W., & Rafiul Biswas, M. (2025). EmoHopeSpeech: An Annotated Dataset of Emotions and Hope Speech in English and Arabic. In G. Angelova, M. Kunilovskaya, M. Escribe, & R. Mitkov (Eds.), Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era, RANLP 2025 (pp. 1406-1412). (International Conference Recent Advances in Natural Language Processing, RANLP). Incoma Ltd. https://doi.org/10.26615/978-954-452-098-4-162

Zaghoauni, Wajdi ; Rafiul Biswas, Md. / EmoHopeSpeech : An Annotated Dataset of Emotions and Hope Speech in English and Arabic. Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era, RANLP 2025. editor / Galia Angelova ; Maria Kunilovskaya ; Marie Escribe ; Ruslan Mitkov. Incoma Ltd, 2025. pp. 1406-1412 (International Conference Recent Advances in Natural Language Processing, RANLP).

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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{\textquoteright} Kappa was employed, revealing 0.75{\textendash}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.",

author = "Wajdi Zaghoauni and \{Rafiul Biswas\}, Md",

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Zaghoauni, W & Rafiul Biswas, M 2025, EmoHopeSpeech: An Annotated Dataset of Emotions and Hope Speech in English and Arabic. in G Angelova, M Kunilovskaya, M Escribe & R Mitkov (eds), Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era, RANLP 2025. International Conference Recent Advances in Natural Language Processing, RANLP, Incoma Ltd, pp. 1406-1412, 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era, RANLP 2025, Varna, Bulgaria, 8/09/25. https://doi.org/10.26615/978-954-452-098-4-162

EmoHopeSpeech: An Annotated Dataset of Emotions and Hope Speech in English and Arabic. / Zaghoauni, Wajdi; Rafiul Biswas, Md.
Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era, RANLP 2025. ed. / Galia Angelova; Maria Kunilovskaya; Marie Escribe; Ruslan Mitkov. Incoma Ltd, 2025. p. 1406-1412 (International Conference Recent Advances in Natural Language Processing, RANLP).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - 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.

AB - 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.

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M3 - Conference contribution

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BT - Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era, RANLP 2025

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A2 - Mitkov, Ruslan

PB - Incoma Ltd

Y2 - 8 September 2025 through 10 September 2025

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Zaghoauni W, Rafiul Biswas M. EmoHopeSpeech: An Annotated Dataset of Emotions and Hope Speech in English and Arabic. In Angelova G, Kunilovskaya M, Escribe M, Mitkov R, editors, Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era, RANLP 2025. Incoma Ltd. 2025. p. 1406-1412. (International Conference Recent Advances in Natural Language Processing, RANLP). doi: 10.26615/978-954-452-098-4-162

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

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