A Federated Approach for Hate Speech Detection
Machine Learning
2023-02-21 v1 Artificial Intelligence
Computation and Language
Abstract
Hate speech detection has been the subject of high research attention, due to the scale of content created on social media. In spite of the attention and the sensitive nature of the task, privacy preservation in hate speech detection has remained under-studied. The majority of research has focused on centralised machine learning infrastructures which risk leaking data. In this paper, we show that using federated machine learning can help address privacy the concerns that are inherent to hate speech detection while obtaining up to 6.81% improvement in terms of F1-score.
Cite
@article{arxiv.2302.09243,
title = {A Federated Approach for Hate Speech Detection},
author = {Jay Gala and Deep Gandhi and Jash Mehta and Zeerak Talat},
journal= {arXiv preprint arXiv:2302.09243},
year = {2023}
}
Comments
EACL 2023 Main Conference (Short Paper)