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Found 4 papers, 2 papers with code
From Languages to Geographies: Towards Evaluating Cultural Bias in Hate Speech Datasets
We find that HS datasets for these languages exhibit a strong geo-cultural bias, largely overrepresenting a handful of countries (e. g., US and UK for English) relative to their prominence in both the broader social media population and the general population speaking these languages.
NaijaHate: Evaluating Hate Speech Detection on Nigerian Twitter Using Representative Data
To address the global issue of hateful content proliferating in online platforms, hate speech detection (HSD) models are typically developed on datasets collected in the United States, thereby failing to generalize to English dialects from the Majority World.
Casteist but Not Racist? Quantifying Disparities in Large Language Model Bias between India and the West
In this paper, we quantify stereotypical bias in popular LLMs according to an Indian-centric frame and compare bias levels between the Indian and Western contexts.
Multilingual Detection of Personal Employment Status on Twitter
Detecting disclosures of individuals' employment status on social media can provide valuable information to match job seekers with suitable vacancies, offer social protection, or measure labor market flows.
