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The Thin Line Between Hate and Profanity

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AI 2019: Advances in Artificial Intelligence (AI 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11919))

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Abstract

Hate speech can be defined as a language used to demean people within a specific group. Hate speech often contains explicitly profane words, however, the presence of these words does not always mean that the text instance is hateful. In some cases, text instances with profane words are just offensive language and they do not target any specific group, and so cannot be classified as hate speech. In this work, we build on existing studies to find a better demarcation between hate speech and offensive language. Our main contribution is to introduce the use of typed dependency as new features in our feature set. This new feature enables us to consider the relationship between long distance words in a text instance, thereby provides more identifying information than single word-based features. We evaluate our approach using a dataset with the classes: hate, offensive and neither. Comparing our work with existing studies, our feature set is much smaller but we achieve better accuracy and show comparable results in further analysis. Our detailed analysis also showed instances missed by the lexical features that were correctly predicted by the proposed feature set.

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Notes

  1. 1.

    http://alt.qcri.org/semeval2019/.

  2. 2.

    https://competitions.codalab.org/competitions/20011.

  3. 3.

    https://help.twitter.com/en/rules-and-policies/hateful-conduct-policy.

  4. 4.

    https://www.facebook.com/communitystandards/hate_speech.

  5. 5.

    The authors have added ‘*’ for public viewing. These were not part of the original tweet.

  6. 6.

    https://spacy.io/.

  7. 7.

    https://spacy.io/api/annotation#dependency-parsing.

  8. 8.

    https://github.com/t-davidson/hate-speech-and-offensive-language.

  9. 9.

    https://hatebase.org/.

  10. 10.

    https://www.figure-eight.com/.

  11. 11.

    https://www.nltk.org/_modules/nltk/stem/wordnet.html.

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Authors and Affiliations

  1. School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand

    Kosisochukwu Judith Madukwe & Xiaoying Gao

Authors
  1. Kosisochukwu Judith Madukwe
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  2. Xiaoying Gao
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Correspondence to Kosisochukwu Judith Madukwe .

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Editors and Affiliations

  1. University of South Australia, Adelaide, SA, Australia

    Jixue Liu

  2. The University of Melbourne, Melbourne, VIC, Australia

    James Bailey

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This work contains examples of hateful and offensive instances. All examples were obtained from the dataset and do not represent the principles of the authors.

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Madukwe, K.J., Gao, X. (2019). The Thin Line Between Hate and Profanity. In: Liu, J., Bailey, J. (eds) AI 2019: Advances in Artificial Intelligence. AI 2019. Lecture Notes in Computer Science(), vol 11919. Springer, Cham. https://doi.org/10.1007/978-3-030-35288-2_28

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  • DOI: https://doi.org/10.1007/978-3-030-35288-2_28

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  • Publisher Name: Springer, Cham

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