Reproduce “Web(er) of Hate: A Survey on How Hate Speech Is Typed” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Luna Wang, Andrew Caines, Alice Hutchings
The authors survey hate-speech datasets, arguing that definitions and labels reflect choices about what a dataset is meant to capture. They frame definitions as analytical lenses, not complete accounts, and recommend documenting assumptions. Across 135 datasets in 36 languages, 71 (53%) adopt prior definitions, 41 (30%) state their own, and 23 (17%) report none; these counts are not model-performance results.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.