Cyberbullying Detection with Fairness Constraints

Understand

Cyberbullying is a widespread adverse phenomenon among online social interactions in today's digital society.

• While numerous computational studies focus on enhancing the cyberbullying detection performance of machine learning algorithms, proposed models tend to carry and reinforce unintended social biases.
• In this study, we try to answer the research question of "Can we mitigate the unintended bias of cyberbullying detection models by guiding the model training with fairness constraints?".
• For this purpose, we propose a model training scheme that can employ fairness constraints and validate our approach with different datasets.