@inproceedings{anjali-etal-2023-unlocking,
    title = "Unlocking Emotions in Text: A Fusion of Word Embeddings and Lexical Knowledge for Emotion Classification",
    author = "Bhardwaj, Anjali  and
      Wasi, Nesar Ahmad  and
      Abulaish, Muhammad",
    editor = "D. Pawar, Jyoti  and
      Lalitha Devi, Sobha",
    booktitle = "Proceedings of the 20th International Conference on Natural Language Processing (ICON)",
    month = dec,
    year = "2023",
    address = "Goa University, Goa, India",
    publisher = "NLP Association of India (NLPAI)",
    url = "https://preview.aclanthology.org/ingest-emnlp/2023.icon-1.78/",
    pages = "766--772",
    abstract = "This paper introduces an improved method for emotion classification through the integration of emotion lexicons and pre-trained word embeddings. The proposed method utilizes semantically similar features to reconcile the semantic gap between words and emotions. The proposed approach is compared against three baselines for predicting Ekman{'}s emotions at the document level on the GoEmotions dataset. The effectiveness of the proposed approach is assessed using standard evaluation metrics, which show at least a 5{\%} gain in performance over baselines."
}