@inproceedings{waseem-hovy-2016-hateful,
    title = "Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on {T}witter",
    author = "Waseem, Zeerak  and
      Hovy, Dirk",
    editor = "Andreas, Jacob  and
      Choi, Eunsol  and
      Lazaridou, Angeliki",
    booktitle = "Proceedings of the {NAACL} Student Research Workshop",
    month = jun,
    year = "2016",
    address = "San Diego, California",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-naloma/N16-2013/",
    doi = "10.18653/v1/N16-2013",
    pages = "88--93",
    abstract = "Hate speech in the form of racist and sexist remarks are a common occurrence on social media. For that reason, many social media services address the problem of identifying hate speech, but the definition of hate speech varies markedly and is largely a manual effort (BBC, 2015; Lomas, 2015). We provide a list of criteria founded in critical race theory, and use them to annotate a publicly available corpus of more than 16k tweets. We analyze the impact of various extra-linguistic features in conjunction with character $n$-grams for hate-speech detection. We also present a dictionary based the most indicative words in our data."
}