mlsanityData to 7 Oct 2026

Understanding and Detecting Dangerous Speech in Social Media

arXiv 2005.06608 ↗First posted 4 May 2020cs.CL cs.LG cs.SIcited by 12

Not on the map. Why?

Abstract (arXiv)

Social media communication has become a significant part of daily activity in modern societies. For this reason, ensuring safety in social media platforms is a necessity. Use of dangerous language such as physical threats in online environments is a somewhat rare, yet remains highly important. Although several works have been performed on the related issue of detecting offensive and hateful language, dangerous speech has not previously been treated in any significant way. Motivated by these observations, we report our efforts to build a labeled dataset for dangerous speech. We also exploit our dataset to develop highly effective models to detect dangerous content. Our best model performs at 59.60% macro F1, significantly outperforming a competitive baseline.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 May 2020.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 2; 2022: 3; 2023: 3; 2024: 3; 2025: 1.

12 papers.