Visual Sentiment Classification of Restaurant Review Images using Deep Convolutional Neural Networks

In the recent years online reviews are prevalent. Over the years people have started giving feedback about a restaurant by posting images as part of a review where the sentiment polarity is classified based on the facial expressions or the foods. Even more to it is a piece of text along with the image that gives more clear understanding about the picture. As there is tremendous work carried over on text sentiment analysis(SA), in this paper we are focusing on visual analysis to identify whether a given image expresses positive or negative sentiment. In this paper, an image sentiment prediction model is built using Convolutional Neural Networks(CNN). The objective of this work is to perform sentiment classification efficiently and enhance the accuracy of restaurant image dataset posted on social media. The results show that the proposed model achieves better performance on analysis of opinions from images compared to naive bayes which is a machine learning technique.