@inproceedings{durairaj-etal-2026-findings,
title = "Findings of the Shared Task on Hope Speech Detection in {T}ulu",
author = "Durairaj, Thenmozhi and
Gowda, Anusha M D and
Adyanthaya, Raksha and
P, Rathnakara Shetty and
Hegde, Parameshwar R and
Aljunid, Mohammed Fadhel and
Kumaresan, Prasanna Kumar and
Chakravarthi, Bharathi Raja",
editor = "Chakravarthi, Bharathi Raja and
Priyadharshini, Ruba and
Madasamy, Anand Kumar and
Thavareesan, Sajeetha and
Rajiakodi, Saranya and
Navaneethakrishnan, Subalalitha and
Chinnappa, Dhivya and
Palani, Balasubramanian and
Subramanian, Malliga and
Shanmugavadivel, Kogilavani and
Rajalakshmi, Ratnavel",
booktitle = "Proceedings of the Sixth Workshop on Speech, Vision, and Language Technologies for {D}ravidian Languages",
month = jul,
year = "2026",
address = "Underline (Virtual)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.dravidianlangtech-1.10/",
pages = "80--87",
ISBN = "979-8-89176-401-9",
abstract = "Hope Speech Identification is the process of detecting positive, supportive, and encouraging language in text. It focuses on identifying content that promotes unity, inclusiveness, and resilience. Identification of hope speech helps supports mental well being, create healthier online environments, counter hate speech, and promote positive digital communication. This shared task hope speech detection in code-mixed Tulu language as part of DravidianLangTech @ ACL 2026, focuses on both the coarse-grained hope tone classification and the fine-grained hope type classification tasks. There are 11 teams participated in the tasks and submitted several runs for both the tasks. The teams are ranked based on the macro-F1 score."
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<abstract>Hope Speech Identification is the process of detecting positive, supportive, and encouraging language in text. It focuses on identifying content that promotes unity, inclusiveness, and resilience. Identification of hope speech helps supports mental well being, create healthier online environments, counter hate speech, and promote positive digital communication. This shared task hope speech detection in code-mixed Tulu language as part of DravidianLangTech @ ACL 2026, focuses on both the coarse-grained hope tone classification and the fine-grained hope type classification tasks. There are 11 teams participated in the tasks and submitted several runs for both the tasks. The teams are ranked based on the macro-F1 score.</abstract>
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%0 Conference Proceedings
%T Findings of the Shared Task on Hope Speech Detection in Tulu
%A Durairaj, Thenmozhi
%A Gowda, Anusha M. D.
%A Adyanthaya, Raksha
%A P, Rathnakara Shetty
%A Hegde, Parameshwar R.
%A Aljunid, Mohammed Fadhel
%A Kumaresan, Prasanna Kumar
%A Chakravarthi, Bharathi Raja
%Y Chakravarthi, Bharathi Raja
%Y Priyadharshini, Ruba
%Y Madasamy, Anand Kumar
%Y Thavareesan, Sajeetha
%Y Rajiakodi, Saranya
%Y Navaneethakrishnan, Subalalitha
%Y Chinnappa, Dhivya
%Y Palani, Balasubramanian
%Y Subramanian, Malliga
%Y Shanmugavadivel, Kogilavani
%Y Rajalakshmi, Ratnavel
%S Proceedings of the Sixth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages
%D 2026
%8 July
%I Association for Computational Linguistics
%C Underline (Virtual)
%@ 979-8-89176-401-9
%F durairaj-etal-2026-findings
%X Hope Speech Identification is the process of detecting positive, supportive, and encouraging language in text. It focuses on identifying content that promotes unity, inclusiveness, and resilience. Identification of hope speech helps supports mental well being, create healthier online environments, counter hate speech, and promote positive digital communication. This shared task hope speech detection in code-mixed Tulu language as part of DravidianLangTech @ ACL 2026, focuses on both the coarse-grained hope tone classification and the fine-grained hope type classification tasks. There are 11 teams participated in the tasks and submitted several runs for both the tasks. The teams are ranked based on the macro-F1 score.
%U https://aclanthology.org/2026.dravidianlangtech-1.10/
%P 80-87
Markdown (Informal)
[Findings of the Shared Task on Hope Speech Detection in Tulu](https://aclanthology.org/2026.dravidianlangtech-1.10/) (Durairaj et al., DravidianLangTech 2026)
ACL
- Thenmozhi Durairaj, Anusha M D Gowda, Raksha Adyanthaya, Rathnakara Shetty P, Parameshwar R Hegde, Mohammed Fadhel Aljunid, Prasanna Kumar Kumaresan, and Bharathi Raja Chakravarthi. 2026. Findings of the Shared Task on Hope Speech Detection in Tulu. In Proceedings of the Sixth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages, pages 80–87, Underline (Virtual). Association for Computational Linguistics.