2025
SemEval
SemEval 2025
SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection
Abstract
AbstractWe 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.
👥
Mega-Team
- 21 authors
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Interdisciplinary Bridge
- Artificial Intelligence and Interdisciplinary and Natural Language Processing
Authors
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,
Saif Mohammad
Topics
Natural Language Processing > Resources & Methods > Multilingual NLP
Interdisciplinary > Linguistics > Computational Linguistics
Interdisciplinary > Social > Affective Computing
Natural Language Processing > Applications > Sentiment Analysis
Machine Learning > Learning Types > Multi-Label Classification
Natural Language Processing > Applications > Emotion Detection