HENIN: Learning Heterogeneous Neural Interaction Networks for Explainable Cyberbullying Detection on Social Media (2020.emnlp-main)
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| Challenge: | Existing methods for detecting cyberbullying rely on text analysis of social media sessions. |
| Approach: | They propose a deep model that uses a comment encoder and a post-comment co-attention sub-network to explain why a media session is identified as cyberbullying. |
| Outcome: | The proposed model outperforms existing models on real datasets and shows evidential comments in the model explainability of cyberbullying detection. |
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