15 lines
1.2 KiB
Markdown
15 lines
1.2 KiB
Markdown
---
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title: Measuring Hate Speech
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link-to-publication: https://arxiv.org/abs/2009.10277
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link-to-data: https://huggingface.co/datasets/ucberkeley-dlab/measuring-hate-speech
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task-description: 10 ordinal labels (sentiment, (dis)respect, insult, humiliation, inferior status, violence, dehumanization, genocide, attack/defense, hate speech), which are debiased and aggregated into a continuous hate speech severity score (hate_speech_score) that includes a region for counterspeech & supportive speeech. Includes 8 target identity groups (race/ethnicity, religion, national origin/citizenship, gender, sexual orientation, age, disability, political ideology) and 42 identity subgroups.
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details-of-task: Hate speech measurement on social media in English
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size-of-dataset: "39,565 comments annotated by 7,912 annotators on 10 ordinal labels, for 1,355,560 total labels."
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percentage-abusive: 25
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language: English
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level-of-annotation: ["Social media comment"]
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platform: ["Twitter", "Reddit", "Youtube"]
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medium: ["Text"]
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reference: "Kennedy, C. J., Bacon, G., Sahn, A., & von Vacano, C. (2020). Constructing interval variables via faceted Rasch measurement and multitask deep learning: a hate speech application. arXiv preprint arXiv:2009.10277."
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