The problem this research addresses is detecting hate speech (HS) in texts in Serbian on the Internet. Detecting and reducing HS is crucial for the safety and well-being of individuals, as it can otherwise lead to real-world harm and tragedies. Traditional methods of manually monitoring online content are time-consuming, costly, and ineffective in dealing with the vast amount of user-generated content. Therefore, there is a need for automated tools that can efficiently detect and prevent HS, which constitutes the primary goal of this research. In this paper, we describe the methods of data collection that we intend to implement, present a short analysis of the existing solutions, and provide the conceptual solution of the model.