Datasets:
Tasks:
Text Classification
Languages:
English
Multilinguality:
monolingual
Annotations Creators:
crowdsourced
Source Datasets:
original
ArXiv:
License:
metadata
tags:
- hate-speech
- counterspeech
- irt
- arxiv:2009.10277
annotations_creators:
- crowdsourced
languages:
- en-US
licenses: []
multilinguality:
- monolingual
pretty_name: measuring-hate-speech
source_datasets:
- original
task_categories:
- text-classification
- text-regression
task_ids:
- hate-speech
- counterspeech
- sentiment-classification
Measuring Hate Speech
This is a public release of the dataset described in Kennedy et al. (2020). The dataset contains one row for each comment that an annotator reviews; each comment is rated multiple times. The primary outcome variable is the "hate speech score" but the 10 constituent labels can also be treated as outcomes.
Key dataset columns
- hate_speech_score - continuous hate speech measure, where higher = more hateful and lower = less hateful
- text - lightly processed text of a social media post
- comment_id - unique ID for each comment
- annotator_id - unique ID for each annotator
- sentiment - ordinal label that is combined into the continuous score
- respect - ordinal label that is combined into the continuous score
- insult - ordinal label that is combined into the continuous score
- humiliate - ordinal label that is combined into the continuous score
- status - ordinal label that is combined into the continuous score
- dehumanize - ordinal label that is combined into the continuous score
- violence - ordinal label that is combined into the continuous score
- genocide - ordinal label that is combined into the continuous score
- attack_defend - ordinal label that is combined into the continuous score
- hatespeech - ordinal label that is combined into the continuous score
- annotator_severity - annotator's estimated survey interpretation bias
Citation
@article{kennedy2020constructing,
title={Constructing interval variables via faceted Rasch measurement and multitask deep learning: a hate speech application},
author={Kennedy, Chris J and Bacon, Geoff and Sahn, Alexander and von Vacano, Claudia},
journal={arXiv preprint arXiv:2009.10277},
year={2020}
}
References
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.