InstaViral AI : A Deep Learning Based System for Intelligent Video Analysis and Content Optimization in Instagram Reels

Abstract

Because short-form video platforms like Instagram Reels are growing so quickly, content producers frequently find it difficult to forecast the performance of their work and lack sophisticated pre-publication optimization tools. Because post-publication measurements are the main emphasis of current analytics, this leads to a crucial gap in the digital content lifecycle. The design and methods for "InstaViral AI", an intelligent video analyzer and content optimizer for Instagram reels are presented in this research. The suggested system analyses multimodal data inputs, such as video frames, audio, captions, and user metadata, by utilizing cutting-edge deep learning (YOLO and MediaPipe) and machine learning approaches (Sci-kit). InstaViral AI will automatically recognize interesting highlights, find the best thumbnail frames, and intelligently recommend enhancements like trending hashtags, better captions, the best times to upload, and the length of the material. InstaViral AI seeks to function as a smart assistant by fusing sentiment analysis, video summarization, and predictive analytics. This will improve content discoverability and lessen the trial-and-error process that is usually involved with social media material.