부산대학교 도서관

Since about a decade ago, deep learning has emerged as a powerful machine learning technique and produced state-of-the-art results in many application domains, ranging from computer vision and speech recognition to NLP. Applying deep learning to sentiment analysis has also become very popular recently. In this paper, we propose a comparative study for multimodal sentiment analysis using deep neural networks involving visual recognition and natural language processing. Initially we make different models for the model using text and another for image and see the results on various models and compare them.