The increasing presence of hate speech (HS) on social media poses significant societal challenges. While efforts in the Natural Language Processing community have focused on automating the detection of explicit forms of HS, subtler and indirect expressions often go unnoticed. This demo introduces PEACE, a novel tool that – besides detecting if a social media message contains explicit or implicit HS – also provides detailed explanations for such predictions.
More specifically, PEACE addresses three main challenging tasks:
- Explores the characteristics of HS messages
- Predicts hatefulness.
- Explains the reasoning behind system predictions.
This project is designed to empower researchers and data scientists by offering a seamless way to explore and discover valuable datasets from the Web. Leveraging a comprehensive collection of 211,894 datasets sourced from HuggingFace (as of June 2024), we provide an intuitive platform for uncovering insights within dataset metadata, such as common tasks and themes.
Our solution features MGExplorer (Menin et al., 2021), a powerful visualization tool that enables users to explore data through interconnected views. This innovative approach allows users to examine datasets from multiple perspectives and zoom in on the most relevant details with ease.
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