Sentiment Analysis Based on Images and Videos

Abstract

Sentiment analysis is process to identify polarity of opinions as positive or negative. Large number of images and videos are being uploaded online every day. Videos and images contain text, visual and audio features that complement each other. Here sentiment analysis of images and video using data of twitter account is performed. Currently many people share images and video without checking content integrity and impact on others. So this framework analyze sentiments of images and videos, then it classify into positive and negative. Based on classification of images and videos we can decide that which content should be forwarded and which should not be allowed to forward. Here we used CNN & RNN to extract features from images and videos and Twitter API to load images from twitter.