A Study of Web 3.0 Blockchain and Natural Learning Process Programming Study: Hate Discourse Detection

As the use of social networking platforms such as Facebook, Twitter, and Instagram increases, so does the prevalence of hate discourse. Hate discourse can be defined as an offensive language addressed at any racial, caste-creed, religious faith, or cultural group. Now, with the open development of Web 3.0, it is difficult to control every element of hate discourse because there is no governing authority. Using Block Chain and Natural Language Programming, this research paper studies an innovative approach for detecting hate discourse on Web 3.0. The proposed study states about blockchain guarantees the rigid and lucidity of data, while NLP algorithms are employed to examine and categorize hateful content online. The study indicates there are models which can be used to detect hate discourse with high accuracy, and the use of blockchain enhances the system's reliability and confidentiality. Thus, the study will identify the models which can mitigate hate discourse on Web 3.0 and may serve as a helpful tool for promoting secure surfing and acceptance of the coexistence of different communities together.