Hate Speech Detection Model on Web 3.0 Based Platform using Blockchain and NLP

Abstract

With the increased usage of social media applications like Facebook, Twitter, or Instagram, hate speech is also rising. Hate speech can be defined as ill talk toward any race, caste, religion, or ethnicity. Now with the new development of web 3.0, which is decentralized, it is challenging to control elements like hate speech because there is no central body that can control it. This research paper presents a novel approach for detecting hate speech on web 3.0-based platforms using blockchain technology and natural language processing (NLP) techniques. The proposed model utilizes blockchain to ensure the immutability and trans-parency of the data, while NLP algorithms are used to analyze and classify the text. The experimental results show that the proposed model achieves high accuracy in detecting hate speech, and the use of blockchain technology enhances the trustworthiness and security of the system. The proposed system can effectively detect and mitigate hate speech on web 3.0-based platforms and may serve as a valuable tool for promoting online safety and inclusivity.