Cross-lingual Hate Speech Detection using Transformer Models

Understand

Hate speech detection within a cross-lingual setting represents a paramount area of interest for all medium and large-scale online platforms.

• Failing to properly address this issue on a global scale has already led over time to morally questionable real-life events, human deaths, and the perpetuation of hate itself.
• This paper illustrates the capabilities of fine-tuned altered multi-lingual Transformer models (mBERT, XLM-RoBERTa) regarding this crucial social data science task with cross-lingual training from English to French, vice-versa and each language on its own, including sections about iterative improvement and comparative error analysis.