Participants are tasked with developing systems that automatically identify emotional content in fragments of historical Spanish letters, addressing issues such as diachronic language variation, historical semantic shifting, and domain adaptation. The shared task aims to foster methodological progress at the intersection of Natural Language Processing (NLP) and Digital Humanities.
🔗 Task page / resources: https://github.com/albinasarymsakova/HISEMOTIONS_2026
Why Participate?
Advance emotion detection methods in low-resource and historical domains.
Explore semantic change effects on automatic classification.
Benchmark systems on a novel historical dataset with expert human annotation.
Cutting-edge research into the computational study of cultural heritage.
Shared Task Details
Task: Multi-label emotion detection
Each text fragment should be labelled with one or more of the following emotions:
• joy • sadness • fear • anger • surprise • hope
Participants will predict binary labels for each emotion per fragment. Systems will be evaluated against hidden gold labels using standard metrics such as precision, recall, and macro-F1 score.
Important Dates
Contact & Submission
For updates, questions, or discussions about the task, please open issues in the task GitHub repository or contact the organisers. Detailed submission guidelines will be published alongside the data releases.
We look forward to your participation and contribution to this exciting challenge!
— HISEMOTIONS 2026 Organising Committee
Dra. Albina Sarymsakova, CSIC-IEGPS-XuGa
Dra. Patricia Martín Rodilla, CSIC-IEGPS-XuGa
Dr. Eugenio Martínez Cámara, Universidad de Jaén
Dr. Alfonso Ureña López, Universidad de Jaén
![]() | Eugenio Martínez Cámara Vicepresidente de la SEPLN | Vice President of the SEPLN. Profesor Titular de Universidad | Associate Professor. Investigador en Proc. del Lenguaje Natural | Postdoctoral Researcher in Natural Language Proc. Código ORCID:0000-0002-5279-8355 Universidad de Jaén Dpto. de Informática | Computer Science Department. Edificio A3, despacho 145 | +34 953212883 ![]() |