Papers by Ahmad Diab
A Weakly Supervised Classifier and Dataset of White Supremacist Language (2023.acl-short)
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| Challenge: | Existing studies on white supremacist language have focused on specific hateful ideologies, but little attention has been given to specific hate speech. |
| Approach: | They propose a weakly supervised classifier for detecting white supremacist language . they use large datasets of white supremacy domains paired with neutral and anti-racist data from similar domains to train the classifiers. |
| Outcome: | The proposed classifiers outperform previous studies on white supremacist classification on unseen datasets and find strong generalization performance for models with weakly annotated data. |