@inproceedings{muhammad-etal-2025-semeval,
title = "{S}em{E}val-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection",
author = "Muhammad, Shamsuddeen Hassan and
Ousidhoum, Nedjma and
Abdulmumin, Idris and
Yimam, Seid Muhie and
Wahle, Jan Philip and
Lima Ruas, Terry and
Beloucif, Meriem and
De Kock, Christine and
Belay, Tadesse Destaw and
Ahmad, Ibrahim Said and
Surange, Nirmal and
Teodorescu, Daniela and
Adelani, David Ifeoluwa and
Aji, Alham Fikri and
Ali, Felermino Dario Mario and
Araujo, Vladimir and
Ayele, Abinew Ali and
Ignat, Oana and
Panchenko, Alexander and
Zhou, Yi and
Mohammad, Saif",
editor = "Rosenthal, Sara and
Ros{\'a}, Aiala and
Ghosh, Debanjan and
Zampieri, Marcos",
booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.semeval-1.327/",
pages = "2558--2569",
ISBN = "979-8-89176-273-2",
abstract = "We present our shared task on text-based emotion detection, covering more than 30 languages from seven distinct language families. These languages are predominantly low-resource and spoken across various continents. The data instances are multi-labeled into six emotional classes, with additional datasets in 11 languages annotated for emotion intensity. Participants were asked to predict labels in three tracks: (a) emotion labels in monolingual settings, (b) emotion intensity scores, and (c) emotion labels in cross-lingual settings."
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<abstract>We present our shared task on text-based emotion detection, covering more than 30 languages from seven distinct language families. These languages are predominantly low-resource and spoken across various continents. The data instances are multi-labeled into six emotional classes, with additional datasets in 11 languages annotated for emotion intensity. Participants were asked to predict labels in three tracks: (a) emotion labels in monolingual settings, (b) emotion intensity scores, and (c) emotion labels in cross-lingual settings.</abstract>
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%0 Conference Proceedings
%T SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection
%A Muhammad, Shamsuddeen Hassan
%A Ousidhoum, Nedjma
%A Abdulmumin, Idris
%A Yimam, Seid Muhie
%A Wahle, Jan Philip
%A Lima Ruas, Terry
%A Beloucif, Meriem
%A De Kock, Christine
%A Belay, Tadesse Destaw
%A Ahmad, Ibrahim Said
%A Surange, Nirmal
%A Teodorescu, Daniela
%A Adelani, David Ifeoluwa
%A Aji, Alham Fikri
%A Ali, Felermino Dario Mario
%A Araujo, Vladimir
%A Ayele, Abinew Ali
%A Ignat, Oana
%A Panchenko, Alexander
%A Zhou, Yi
%A Mohammad, Saif
%Y Rosenthal, Sara
%Y Rosá, Aiala
%Y Ghosh, Debanjan
%Y Zampieri, Marcos
%S Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-273-2
%F muhammad-etal-2025-semeval
%X We present our shared task on text-based emotion detection, covering more than 30 languages from seven distinct language families. These languages are predominantly low-resource and spoken across various continents. The data instances are multi-labeled into six emotional classes, with additional datasets in 11 languages annotated for emotion intensity. Participants were asked to predict labels in three tracks: (a) emotion labels in monolingual settings, (b) emotion intensity scores, and (c) emotion labels in cross-lingual settings.
%U https://aclanthology.org/2025.semeval-1.327/
%P 2558-2569
Markdown (Informal)
[SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection](https://aclanthology.org/2025.semeval-1.327/) (Muhammad et al., SemEval 2025)
ACL
- Shamsuddeen Hassan Muhammad, Nedjma Ousidhoum, Idris Abdulmumin, Seid Muhie Yimam, Jan Philip Wahle, Terry Lima Ruas, Meriem Beloucif, Christine De Kock, Tadesse Destaw Belay, Ibrahim Said Ahmad, Nirmal Surange, Daniela Teodorescu, David Ifeoluwa Adelani, Alham Fikri Aji, Felermino Dario Mario Ali, Vladimir Araujo, Abinew Ali Ayele, Oana Ignat, Alexander Panchenko, Yi Zhou, and Saif Mohammad. 2025. SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection. In Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025), pages 2558–2569, Vienna, Austria. Association for Computational Linguistics.