Shared-Tasks

Chinese Dimensional Aspect-Based Sentiment Analysis (dimABSA)

Aspect-Based Sentiment Analysis (ABSA) is a critical NLP research topic that aims to identify the aspects of a given sentence and analyze the sentiments associated with each aspect. Compared to representing affective states as several discrete classes (i.e., polarity), the dimensional approach that represents affective states as continuous numerical values (called intensity) in multiple dimensions, such as valence-arousal (VA) space, provides more fine-grained emotional information. Therefore, we organize a Chinese dimensional ABSA shared task (dimABSA) in the SIGHAN 2024 workshop, providing fine-grained sentiment intensity prediction for each extracted aspect of a restaurant review. We have three subtasks: 1) Intensity Prediction, 2) Triplet Extraction, and 3) Quadruple Extraction. Participants will be free to choose the subtasks they wish to participate in.

More information is available online at https://dimabsa2024.github.io/

Important Dates:

Shared Task Organizers:Â