Multi-cultural Abusive and Hate Speech Detection

Mon, 02 Mar 2026 00:00:00 +0000

Context

What counts as abusive or hate speech depends on the socio-cultural context: the culture, norms, and laws of the people who read a text. The same text might be deemed offensive in one culture, allowed in another, and legally prosecutable in a third. A detection model is a machine learning model that flags a text as abusive or hate speech. It learns from labeled examples.

Objective

This proposal evaluates how different definitions of abusive and hate speech affect detection models. The aim is to promote awareness when developing accurate detection models.

One text judged in three socio-cultural contexts, each with its own definition of abusive and hate speech. Cultures A, B, and C are placeholders, not real cultures.

Abusive Language | Language Technologies Lab

Multi-cultural Abusive and Hate Speech Detection

Context

Objective