Behind Closed Words: Creating and Investigating the forePLay Annotated Dataset for Polish Erotic Discourse
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866910981472387072 |
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| author | Kołos, Anna Lorenc, Katarzyna Wiśnios, Emilia Karlińska, Agnieszka |
| author_facet | Kołos, Anna Lorenc, Katarzyna Wiśnios, Emilia Karlińska, Agnieszka |
| contents | The surge in online content has created an urgent demand for robust detection systems, especially in non-English contexts where current tools demonstrate significant limitations. We present forePLay, a novel Polish language dataset for erotic content detection, featuring over 24k annotated sentences with a multidimensional taxonomy encompassing ambiguity, violence, and social unacceptability dimensions. Our comprehensive evaluation demonstrates that specialized Polish language models achieve superior performance compared to multilingual alternatives, with transformer-based architectures showing particular strength in handling imbalanced categories. The dataset and accompanying analysis establish essential frameworks for developing linguistically-aware content moderation systems, while highlighting critical considerations for extending such capabilities to morphologically complex languages. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_17533 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Behind Closed Words: Creating and Investigating the forePLay Annotated Dataset for Polish Erotic Discourse Kołos, Anna Lorenc, Katarzyna Wiśnios, Emilia Karlińska, Agnieszka Computation and Language The surge in online content has created an urgent demand for robust detection systems, especially in non-English contexts where current tools demonstrate significant limitations. We present forePLay, a novel Polish language dataset for erotic content detection, featuring over 24k annotated sentences with a multidimensional taxonomy encompassing ambiguity, violence, and social unacceptability dimensions. Our comprehensive evaluation demonstrates that specialized Polish language models achieve superior performance compared to multilingual alternatives, with transformer-based architectures showing particular strength in handling imbalanced categories. The dataset and accompanying analysis establish essential frameworks for developing linguistically-aware content moderation systems, while highlighting critical considerations for extending such capabilities to morphologically complex languages. |
| title | Behind Closed Words: Creating and Investigating the forePLay Annotated Dataset for Polish Erotic Discourse |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2412.17533 |