@inproceedings{amal-etal-2024-anlp,
    title = "{ANLP} {RG} at {S}tance{E}val2024: Comparative Evaluation of Stance, Sentiment and Sarcasm Detection",
    author = "Amal, Mezghani  and
      Boujelbane, Rahma  and
      Ellouze, Mariem",
    editor = "Habash, Nizar  and
      Bouamor, Houda  and
      Eskander, Ramy  and
      Tomeh, Nadi  and
      Abu Farha, Ibrahim  and
      Abdelali, Ahmed  and
      Touileb, Samia  and
      Hamed, Injy  and
      Onaizan, Yaser  and
      Alhafni, Bashar  and
      Antoun, Wissam  and
      Khalifa, Salam  and
      Haddad, Hatem  and
      Zitouni, Imed  and
      AlKhamissi, Badr  and
      Almatham, Rawan  and
      Mrini, Khalil",
    booktitle = "Proceedings of the Second Arabic Natural Language Processing Conference",
    month = aug,
    year = "2024",
    address = "Bangkok, Thailand",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2024.arabicnlp-1.90/",
    doi = "10.18653/v1/2024.arabicnlp-1.90",
    pages = "788--793",
    abstract = "As part of our study, we worked on three tasks:stance detection, sarcasm detection and senti-ment analysis using fine-tuning techniques onBERT-based models. Fine-tuning parameterswere carefully adjusted over multiple iterationsto maximize model performance. The threetasks are essential in the field of natural lan-guage processing (NLP) and present uniquechallenges. Stance detection is a critical taskaimed at identifying a writer`s stances or view-points in relation to a topic. Sarcasm detectionseeks to spot sarcastic expressions, while senti-ment analysis determines the attitude expressedin a text. After numerous experiments, we iden-tified Arabert-twitter as the model offering thebest performance for all three tasks. In particu-lar, it achieves a macro F-score of 78.08{\%} forstance detection, a macro F1-score of 59.51{\%}for sarcasm detection and a macro F1-score of64.57{\%} for sentiment detection. .Our source code is available at https://github.com/MezghaniAmal/Mawqif"
}