Team DiSaster at SemEval-2020 Task 11: Combining BERT and hand-crafted Features for Identifying Propaganda Techniques in News

Anders Kaas, Viktor Torp Thomsen, Barbara Plank

    Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

    Abstract

    The identification of communication techniques in news articles such as propaganda is important, as such techniques can influence the opinions of large numbers of people. Most work so far focused on the identification at the news article level. Recently, a new dataset and shared task has been proposed for the identification of propaganda techniques at the finer-grained span level. This paper describes our system submission to the subtask of technique classification (TC) for the SemEval 2020 shared task on detection of propaganda techniques in news articles. We propose a method of combining neural BERT representations with hand-crafted features via stacked generalization. Our model has the added advantage that it combines the power of contextual representations from BERT with simple span-based and article-based global features. We present an ablation study which shows that even though BERT representations are very powerful also for this task, BERT still benefits from being combined with carefully designed task-specific features.
    OriginalsprogEngelsk
    TitelSemEval 2020
    ForlagAssociation for Computational Linguistics
    Publikationsdato2020
    StatusUdgivet - 2020

    Emneord

    • Propaganda detection
    • Span-level classification
    • Neural BERT representations
    • Hand-crafted features
    • Stacked generalization

    Fingeraftryk

    Dyk ned i forskningsemnerne om 'Team DiSaster at SemEval-2020 Task 11: Combining BERT and hand-crafted Features for Identifying Propaganda Techniques in News'. Sammen danner de et unikt fingeraftryk.

    Citationsformater