arXiv Computation and Language
3d ago

When Hate Meets Facts: LLMs-in-the-Loop for Check-worthiness Detection in Hate Speech

The paper introduces WSF-ARG+, a new dataset that pairs hate speech with check‑worthiness annotations, and presents an LLM‑in‑the‑loop framework to streamline the annotation process. Experiments with 12 open‑weight large language models demonstrate that the framework cuts human effort while maintaining annotation quality. The study also shows that incorporating check‑worthiness labels improves hate‑speech detection performance, boosting macro‑F1 scores for large models by up to 0.213 and averaging 0.154 across models.

By Nicol\'as Benjam\'in Ocampo, Tommaso Caselli, Davide Ceolin
arXiv AI
Jul 21

Posts of Peril: Detecting Information About Hazards in Text

arXiv:2405. 17838v3 Announce Type: replace-cross Abstract: Socio-linguistic indicators of affectively-relevant phenomena, such as emotion or sentiment, are often extracted from text to better understand features of human-computer interactions, including on social media.

By Keith Burghardt, Daniel M. T. Fessler, Chyna Tang, Anne Pisor, Kristina Lerman