tasksource/measuring-hate-speech-votes
measuring-hate-speech-votes Measuring Hate Speech (Kennedy et al., 2020; Sachdeva et al., 2022), one row per comment with vote counts. The source has one row per (comment, annotator). Each survey item becomes a list of vote counts over its ordinal codes, in code order: 0-4 for the nine Likert items, where a higher code is more hateful (sentiment: strongly positive to strongly negative; respect: strongly respectful to strongly disrespectful; insult, humiliate, dehumanize… See the full description on the dataset page: https://huggingface.co/datasets/tasksource/measuring-hate-speech-votes.
measuring-hate-speech-votes
Measuring Hate Speech (Kennedy et al., 2020; Sachdeva et al., 2022), one row per comment with vote counts.
The source has one row per (comment, annotator). Each survey item becomes a list of vote counts over its ordinal codes, in code order: 0-4 for the nine Likert items, where a higher code is more hateful (sentiment: strongly positive to strongly negative; respect: strongly respectful to strongly disrespectful; insult, humiliate, dehumanize, violence, genocide: strongly disagree to strongly agree; status: strongly superior to strongly inferior; attack_defend: strongly defending to strongly attacking), and 0-2 for hatespeech (no, unclear, yes). Survey wording: Sachdeva et al. (2022), appendix table 1. Comments with fewer than three annotators are dropped; rows are split 90/5/5 by a hash of the comment id. License: CC BY 4.0, as the original.
Original data: ucberkeley-dlab/measuring-hate-speech. Repackaged as parquet for tasksource by scripts/upload_repackaged.py.