Source-driven Representations for Hate Speech Detection

Flavio Merenda, Claudia Zaghi, Tomasso Caselli, Malvina Nissim

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    Abstract

    Sources, in the form of selected Facebook pages, can be used as indicators of hate-rich content. Polarized distributed representations created over such content prove superior to generic embeddings in the task of hate speech detection. The same content seems to carry a too weak signal to proxy silver labels in a distant supervised setting. However, this signal is stronger than gold labels which come from a different distribution, leading to re-think the process of annotation in the context of highly subjective judgments.
    Original languageEnglish
    Title of host publicationProceedings of the Fifth Italian Conference on Computational Linguistics (CLiC-it 2018)
    EditorsTomasso Caselli, Nicole Noviell, Viviana Patti, Paolo Rosso
    Number of pages6
    Publication statusPublished - 2018
    EventEVALITA 2018 - CLIC-It 2018, Turin, Italy
    Duration: 12-Dec-201813-Dec-2018

    Publication series

    Name
    Volume2253
    ISSN (Electronic)1613-0073

    Workshop

    WorkshopEVALITA 2018
    CountryItaly
    CityTurin
    Period12/12/201813/12/2018

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