@inproceedings{hassan-etal-2021-asad,
    title = "{ASAD}: {A}rabic Social media Analytics and un{D}erstanding",
    author = "Hassan, Sabit  and
      Mubarak, Hamdy  and
      Abdelali, Ahmed  and
      Darwish, Kareem",
    booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations",
    month = apr,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.eacl-demos.14",
    doi = "10.18653/v1/2021.eacl-demos.14",
    pages = "113--118",
    abstract = "This system demonstration paper describes ASAD: Arabic Social media Analysis and unDerstanding, a suite of seven individual modules that allows users to determine dialects, sentiment, news category, offensiveness, hate speech, adult content, and spam in Arabic tweets. The suite is made available through a web API and a web interface where users can enter text or upload files.",
}