Cyberbullying detection across social media platforms via platform-aware adversarial encoding

Peiling Yi, Arkaitz Zubiaga

ICWSM. 2022.

Despite the increasing interest in cyberbullying detection, existing efforts have largely been limited to experiments on a single platform and their generalisability across different social media platforms has received less attention. We propose XP-CB, a novel cross-platform framework based on Transformers and adversarial learning. XP-CB can enhance a Transformer leveraging unlabelled data from the source and target platforms to come up with a common representation while preventing platform-specific training. To validate our proposed framework, we experiment on cyberbullying datasets from three different platforms through six cross-platform configurations, showing its effectiveness with both BERT and RoBERTa as the underlying Transformer models.

@inproceedings{yi2022cyberbullying,
  title={Cyberbullying detection across social media platforms via platform-aware adversarial encoding},
  author={Yi, Peiling and Zubiaga, Arkaitz},
  booktitle={Proceedings of the International AAAI Conference on Web and Social Media},
  volume={16},
  pages={1430--1434},
  year={2022}
}