Multimodal Content Analysis and Classification Approach (MCACA)

Abstract

The proliferation of online video platforms has transformed how information is disseminated, offering unprecedented access to a vast array of content. However, this accessibility also brings with it the challenge of identifying and filtering out harmful videos that may contain unethical or inappropriate content. In this work, it presents an advanced method that combines natural language processing (NLP) and machine learning techniques to detect and classify harmful videos effectively. This approach involves converting video content into structured text data, analyzing it using NLP algorithms, and employing machine learning classifiers to categorize videos based on their ethical implications. By leveraging these techniques, it aims to provide a robust solution for identifying and mitigating the impact of harmful content on online platforms.