1 code implementation • 7 Feb 2023 • Kailai Yang, Tianlin Zhang, Hassan Alhuzali, Sophia Ananiadou
To address these issues, we propose a novel low-dimensional Supervised Cluster-level Contrastive Learning (SCCL) method, which first reduces the high-dimensional SCL space to a three-dimensional affect representation space Valence-Arousal-Dominance (VAD), then performs cluster-level contrastive learning to incorporate measurable emotion prototypes.
1 code implementation • EACL 2021 • Hassan Alhuzali, Sophia Ananiadou
We propose a new model "SpanEmo" casting multi-label emotion classification as span-prediction, which can aid ER models to learn associations between labels and words in a sentence.
Ranked #1 on Emotion Classification on SemEval 2018 Task 1E-c
no code implementations • WS 2019 • Hassan Alhuzali, Sophia Ananiadou
The availability of large-scale and real-time data on social media has motivated research into adverse drug reactions (ADRs).
no code implementations • WS 2018 • Hassan Alhuzali, Mohamed Elaraby, Muhammad Abdul-Mageed
We also offer an analysis of system performance and the impact of training data size on the task.
no code implementations • WS 2018 • Hassan Alhuzali, Muhammad Abdul-Mageed, Lyle Ungar
The computational treatment of emotion in natural language text remains relatively limited, and Arabic is no exception.