@inproceedings{nabhani-etal-2025-integrating,
    title = "Integrating Argumentation Features for Enhanced Propaganda Detection in {A}rabic Narratives on the Israeli War on {G}aza",
    author = "Nabhani, Sara  and
      Borg, Claudia  and
      Micallef, Kurt  and
      Al-Khatib, Khalid",
    editor = "Jarrar, Mustafa  and
      Habash, Habash  and
      El-Haj, Mo",
    booktitle = "Proceedings of the first International Workshop on Nakba Narratives as Language Resources",
    month = jan,
    year = "2025",
    address = "Abu Dhabi",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2025.nakbanlp-1.14/",
    pages = "127--149",
    abstract = "Propaganda significantly shapes public opinion, especially in conflict-driven contexts like the Israeli-Palestinian conflict. This study explores the integration of argumentation features, such as claims, premises, and major claims, into machine learning models to enhance the detection of propaganda techniques in Arabic media. By leveraging datasets annotated with fine-grained propaganda techniques and employing crosslingual and multilingual NLP methods, along with GPT-4-based annotations, we demonstrate consistent performance improvements. A qualitative analysis of Arabic media narratives on the Israeli war on Gaza further reveals the model{'}s capability to identify diverse rhetorical strategies, offering insights into the dynamics of propaganda. These findings emphasize the potential of combining NLP with argumentation features to foster transparency and informed discourse in politically charged settings."
}