2025
ACL
ACL 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
🌉
Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning and Natural Language Processing
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio
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