no code implementations • 27 Apr 2024 • Manuel Tonneau, Diyi Liu, Samuel Fraiberger, Ralph Schroeder, Scott A. Hale, Paul Röttger
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.
1 code implementation • 28 Mar 2024 • Manuel Tonneau, Pedro Vitor Quinta de Castro, Karim Lasri, Ibrahim Farouq, Lakshminarayanan Subramanian, Victor Orozco-Olvera, Samuel Fraiberger
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.
no code implementations • 15 Sep 2023 • Khyati Khandelwal, Manuel Tonneau, Andrew M. Bean, Hannah Rose Kirk, Scott A. Hale
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.
1 code implementation • ACL 2022 • Manuel Tonneau, Dhaval Adjodah, João Palotti, Nir Grinberg, Samuel Fraiberger
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.