@inproceedings{gaanoun-benelallam-2022-si2m,
    title = "{SI}2{M} {\&} {AIOX} Labs at {WANLP} 2022 Shared Task: Propaganda Detection in {A}rabic, A Data Augmentation and Name Entity Recognition Approach",
    author = "Gaanoun, Kamel  and
      Benelallam, Imade",
    editor = "Bouamor, Houda  and
      Al-Khalifa, Hend  and
      Darwish, Kareem  and
      Rambow, Owen  and
      Bougares, Fethi  and
      Abdelali, Ahmed  and
      Tomeh, Nadi  and
      Khalifa, Salam  and
      Zaghouani, Wajdi",
    booktitle = "Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP)",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates (Hybrid)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2022.wanlp-1.58/",
    doi = "10.18653/v1/2022.wanlp-1.58",
    pages = "506--510",
    abstract = "This paper presents SI2M {\&} AIOX Labs work among the propaganda detection in Arabic text shared task. The objective of this challenge is to identify the propaganda techniques used in specific propaganda fragments. We use a combination of data augmentation, Name Entity Recognition, rule-based repetition detection, and ARBERT prediction to develop our system. The model we provide scored 0.585 micro F1-Score and ranked 6th out of 12 teams."
}