We invite you to participate in the shared task on Multi-Label and Multi-Class Emotion Classification on Code-Mixed Text Messages, organized as part of WASSA 2023 https://wassa-workshop.github.io/at ACL 2023 https://2023.aclweb.org/. This task aims to develop models that can predict emotion based on code-mixed (Roman Urdu and English) text messages.
*Task Description*
The shared task has two Tracks:
*Track 1 - Multi-Label Emotion Classification (MLEC):* Given a code-mixed SMS message, classify it as 'neutral or no emotion' or as one, or more, of eleven given emotions that best represent the mental state of the author.
*Track 2 - Multi-Class Emotion Classification (MCEC):* Given a code-mixed SMS message, classify it as 'neutral or no emotion' or as one of eleven given emotions that best represent the mental state of the author.
*Note: *You are free to participate in any or both tracks.
*For participation, please check:* https://codalab.lisn.upsaclay.fr/competitions/10864
*Important Dates*
- February 28th, 2023: Initial training data release - February 28th, 2023: Codalab competition website goes online, and development data released - April 15th, 2023: Evaluation phase begins: development labels test data released - April 18th, 2023: Deadline submission of final result on Codalab - April 24th, 2023: Deadline system description paper (max. 4p) - May 22nd, 2023: Notification of acceptance - June 6th, 2023: Camera-ready papers due
*Task Organizers*
- Iqra Ameer - School of Biomedical Informatics, University of Texas, Health Science Center Houston, USA - Necva Bölücü - Commonwealth Scientific and Industrial Research Organisation, Australia - Ali Al Bataineh - Department of Electrical and Computer Engineering Norwich University, USA - Hua Xu - Section of Biomedical Informatics and Data Science, School of Medicine, Yale University, USA
*Contact*
wassa23codemixed [at] gmail [dot] com
*Join Google Group*
wassa23codemixed@googlegroups.com