Hope Speech Detection: A Comparative Study across Four Languages
DOI:
https://doi.org/10.61467/2007.1558.2026.v17i2.1279Keywords:
transformer-based models, Hope Speech Detection, Ridge ClassifierAbstract
This paper presents a multilingual approach to hope speech detection using both traditional machine learning (Ridge Classifier with TF-IDF) and transformer-based models (LaBSE). We evaluate performance across four languages English, Spanish, Urdu, and German using the PolyHope dataset. Experimental results demonstrate that LaBSE consistently outperforms the Ridge baseline, particularly in low-resource settings like Urdu. Our findings highlight the effectiveness of multilingual transformers in capturing nuanced expressions of hope across diverse linguistic and cultural contexts.
Smart citations: https://scite.ai/reports/10.61467/2007.1558.2026.v17i2.1279
Dimensions.
Open Alex.
References
Abdullah, A., Hafeez, N., Sardar, K., Oropeza Rodríguez, J. L., Gelbukh, A., & Sidorov, G. (2023). Integration of agile approaches with quantum high-performance computing in healthcare system designs. Computación y Sistemas, 29(3). https://doi.org/10.13053/cys-29-3-5810
Abdullah, A., Ullah, F., Hafeez, N., Latif, I., Sidorov, G., Riverón, E. F., & Gelbukh, A. (2023). Cyberbullying detection on social media using machine learning techniques. Computación y Sistemas, 29(3). https://doi.org/10.13053/cys-29-3-5481
Abiola, T., Ojo, O. E., Sidorov, G., Kolesnikova, O., & Calvo, H. (2025, July). CIC-IPN at SemEval-2025 Task 11: Transformer-based approach to multi-class emotion. In Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025).
Achamaleh, T., Abiola, T. O., Kawo, L. E., Mebraihtu, M., & Sidorov, G. (2025). CIC-NLP @ DravidianLangTech 2025: Detecting AI-generated product reviews in Dravidian languages. In Proceedings of the Fifth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages.
Aggarwal, P., Das, A., & Chakravarthi, B. R. (2023). Multilingual hope-speech detection using transformer-based models. In Proceedings of the Third Workshop on Language Technology for Equality, Diversity and Inclusion (LT-EDI 2023). Association for Computational Linguistics. https://aclanthology.org/2023.ltedi-1.38
Ahmad, M., Shahiki-Tash, M., Jamshidi, A., et al. (2024). Analyzing hope speech from psycholinguistic and emotional perspectives. Scientific Reports, 14, 23548. https://doi.org/10.1038/s41598-024-74630-y
Ahmad, M., Shahiki-Tash, M., Jamshidi, A., et al. (2024). Analyzing hope speech from psycholinguistic and emotional perspectives. Scientific Reports, 14, 23548. https://doi.org/10.1038/s41598-024-74630-y
Balouchzahi, F., Sidorov, G., & Gelbukh, A. (2022). PolyHope: Two-level hope speech detection from tweets (arXiv:2210.14136). arXiv. https://arxiv.org/abs/2210.14136
Balouchzahi, F., Sidorov, G., & Gelbukh, A. (2023). PolyHope: Two-level hope speech detection from tweets. Expert Systems with Applications, 225, 120078. https://doi.org/10.1016/j.eswa.2023.120078
Bruininks, P., & Malle, B. F. (2005). Distinctive features of hope and related emotions. Cognition & Emotion, 19(2), 113–142. https://doi.org/10.1080/02699930441000292
Butt, S., Balouchzahi, F., Amjad, A. I., Amjad, M., Ceballos, H. G., & Jiménez-Zafra, S. M. (2025a). Optimism, expectation, or sarcasm? Multi-class hope-speech detection in Spanish and English (arXiv:2504.17974). arXiv. https://arxiv.org/abs/2504.17974
Butt, S., Balouchzahi, F., Amjad, M., Jiménez-Zafra, S. M., Ceballos, H. G., & Sidorov, G. (2025b). Overview of PolyHope at IberLEF 2025: Optimism, expectation or sarcasm? Procesamiento del Lenguaje Natural, 75, 461–474.
Chakravarthi, B. R. (2020). HopeEDI: A multilingual hope-speech detection dataset for equality, diversity, and inclusion. In Proceedings of the Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media (PEOPLES 2020) (pp. 41–53). Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.peoples-1.5
Chakravarthi, B. R. (2022). Hope-speech detection in YouTube comments. Social Network Analysis and Mining, 12(1), 75. https://doi.org/10.1007/s13278-022-00901-z
Chakravarthi, B. R., & Muralidaran, V. (2021). Findings of the shared task on hope speech detection for equality, diversity, and inclusion. In Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion (LT-EDI 2021) (pp. 61–72). Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.ltedi-1.8
CodaBench. (2025). PolyHope at IberLEF 2025: Optimism, expectation or sarcasm? https://www.codabench.org/competitions/5509/
Diener, E. (2009). The science of well-being: The collected works of Ed Diener. Springer.
García-Baeza, D., García-Cumbreras, M. Á., Jiménez-Zafra, S. M., García-Díaz, J. A., & Valencia-García, R. (2023). Hope speech detection in Spanish: The LGBT case. Language Resources and Evaluation, 57, 1487–1514. https://doi.org/10.1007/s10579-023-09638-3
Guerrero-Rangel, J. R. G., Sidorov, G., Maldonado-Sifuentes, C. E., Vargas-Santiago, M., Ortega-García, M. C., & León-Velasco, D. A. (2024). Natural language processing approach using a neural network ensemble (CNN-HSNN) for skin cancer and multi-disease classification. Computación y Sistemas, 28(3). https://doi.org/10.13053/cys-28-3-5015
Jiménez-Zafra, S. M., et al. (2023). Overview of HOPE@IberLEF 2023: Multilingual hope-speech detection. Procesamiento del Lenguaje Natural, 71, 289–300. https://doi.org/10.26342/2023-71-29
Khanna, P., Das, A., & Chakravarthi, B. R. (2022). Transformer-based approaches for hope-speech detection. In Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion (LT-EDI 2022) (pp. 423–431). Association for Computational Linguistics. https://aclanthology.org/2022.ltedi-1.49
O’Hara, D. J. (2021). Three spheres of hope: Generalised, particularised and transformative. In L. Ortiz & D. O’Hara (Eds.), Phoenix rising from contemporary global society (pp. 3–14). Brill.
Oladepo, T., Abiola, O., Abiola, T., Abdullah, A., Muhammad, U., & Abiola, B. (2025, July). Predicting emotion intensity in text using transformers. In Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025).
Palakodety, S., KhudaBukhsh, A. R., & Carbonell, J. G. (2019). Hope-speech detection: Helping online communities become more inclusive. In Proceedings of the 10th ACM Conference on Web Science (pp. 235–243). Association for Computing Machinery. https://doi.org/10.1145/3292522.3326032
Riloff, E., Qadir, A., Surve, P., De Silva, L., Gilbert, N., & Huang, R. (2013). Sarcasm as contrast between a positive sentiment and negative situation. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (pp. 704–714). Association for Computational Linguistics.
Sidorov, G., Balouchzahi, F., Ramos, L., Gómez-Adorno, H., & Gelbukh, A. (2025). Multilingual identification of nuanced dimensions of hope speech in social-media texts (MIND-HOPE). Scientific Reports, 15(1), 26783. https://doi.org/10.1038/s41598-025-10683-x
Snyder, C. R. (2002). Hope theory: Rainbows in the mind. Psychological Inquiry, 13(4), 249–275. https://doi.org/10.1207/S15327965PLI1304_01
Snyder, C. R., Harris, C., Anderson, J. R., et al. (1991). The will and the ways: Development and validation of an individual-differences measure of hope. Journal of Personality and Social Psychology, 60(4), 570–585. https://doi.org/10.1037/0022-3514.60.4.570
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 International Journal of Combinatorial Optimization Problems and Informatics
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
