@inproceedings{soma-etal-2023-identifying,
    title = "Identifying Correlation between Sentiment Analysis and Septic News Sentences Classification Tasks",
    author = "Das, Soma  and
      Ghosh, Sagarika  and
      Chatterji, Sanjay",
    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/jlcl-multiple-ingestion/2023.icon-1.74/",
    pages = "738--742",
    abstract = "This research investigates the correlation between Sentiment and SEPSIS(SpEculation, oPinion, biaS, and twISt) characteristics in news sentences through an ablation study. Various Sentiment analysis models, including TextBlob, Vader, and RoBERTa, are examined to discern their impact on news sentences. Additionally, we explore the Logistic Regression(LR), Decision Trees(DT), Support Vector Machines(SVM) and Convolutional Neural Network (CNN) models for Septic sentence classification."
}