Papers by Oguzhan Ulucan
Towards Explainable Hate Speech Detection (2025.findings-acl)
Copied to clipboard
| Challenge: | Recent advances in deep learning have significantly enhanced the efficiency and accuracy of natural language processing (NLP) tasks. |
| Approach: | They propose a model that uses valence, arousal, and dominance (VAD) scores to detect hate speech and a weighted sum of valent, valance, and valency (VA) scores for classification. |
| Outcome: | The proposed model can compete with state-of-the-art models in detecting hate speech and non-hate speech words based on their individual and summed VAD-values. |