This research investigates current state of hate speech moderation in the landscape of social media platforms particularly for the extend of explainability and trust. There is a need to address the lack of explainability in monitoring hate speech on social media. This involves using XAI as a bridge between the application of Machine Learning in the problem domain and to ensure the compliance of any AI model with established domain knowledge in the field. Establishing a certain level of trust between the system and its stakeholders is a genuine requirement. Similarly, explainability enables policymakers to develop better policies with an increased understanding of the system.