VISU at WASSA 2023 Shared Task: Detecting Emotions in Reaction to News
  Stories Leveraging BERT and Stacked Embeddings
Vivek Kumar Sushmita Singh Prayag Tiwari
Our system, VISU, participated in the WASSA 2023 Shared Task (3) of Emotion
Classification from essays written in reaction to news articles. Emotion
detection from complex dialogues is challenging and often requires
context/domain understanding. Therefore in this research, we have focused on
developing deep learning (DL) models using the combination of word embedding
representations with tailored prepossessing strategies to capture the nuances
of emotions expressed. Our experiments used static and contextual embeddings
(individual and stacked) with Bidirectional Long short-term memory (BiLSTM) and
Transformer based models. We occupied rank tenth in the emotion detection task
by scoring a Macro F1-Score of 0.2717, validating the efficacy of our
implemented approaches for small and imbalanced datasets with mixed categories
of target emotions.