A Weakly Supervised Classifier and Dataset of White Supremacist Language
Computation and Language
2023-06-29 v1
Abstract
We present a dataset and classifier for detecting the language of white supremacist extremism, a growing issue in online hate speech. Our weakly supervised classifier is trained on large datasets of text from explicitly white supremacist domains paired with neutral and anti-racist data from similar domains. We demonstrate that this approach improves generalization performance to new domains. Incorporating anti-racist texts as counterexamples to white supremacist language mitigates bias.
Cite
@article{arxiv.2306.15732,
title = {A Weakly Supervised Classifier and Dataset of White Supremacist Language},
author = {Michael Miller Yoder and Ahmad Diab and David West Brown and Kathleen M. Carley},
journal= {arXiv preprint arXiv:2306.15732},
year = {2023}
}
Comments
ACL 2023 short