@inproceedings{ghoul-lejeune-2021-sarcasm,
    title = "Sarcasm and Sentiment Detection in {A}rabic: investigating the interest of character-level features",
    author = {Ghoul, Dhaou  and
      Lejeune, Ga{\"e}l},
    editor = "Habash, Nizar  and
      Bouamor, Houda  and
      Hajj, Hazem  and
      Magdy, Walid  and
      Zaghouani, Wajdi  and
      Bougares, Fethi  and
      Tomeh, Nadi  and
      Abu Farha, Ibrahim  and
      Touileb, Samia",
    booktitle = "Proceedings of the Sixth Arabic Natural Language Processing Workshop",
    month = apr,
    year = "2021",
    address = "Kyiv, Ukraine (Virtual)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2021.wanlp-1.41/",
    pages = "329--333",
    abstract = "We present three methods developed for the Shared Task on Sarcasm and Sentiment Detection in Arabic. We present a baseline that uses character n-gram features. We also propose two more sophisticated methods: a recurrent neural network with a word level representation and an ensemble classifier relying on word and character-level features. We chose to present results from an ensemble classifier but it was not very successful as compared to the best systems : 22th/37 on sarcasm detection and 15th/22 on sentiment detection. It finally appeared that our baseline could have been improved and beat those results."
}