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2018 | OriginalPaper | Chapter

Image Sentiment Analysis Using Convolutional Neural Network

Authors : Akshi Kumar, Arunima Jaiswal

Published in: Intelligent Systems Design and Applications

Publisher: Springer International Publishing

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Abstract

Visual media is one of the most powerful channel for expressing emotions and sentiments. Social media users are gradually using multimedia like images, videos etc. for expressing their opinions, views and experiences. Sentiment analysis of this vast user generated visual content can aid in better and improved extraction of user sentiments. This motivated us to focus on determining ‘image sentiment analyses’. Significant advancement has been made in this area, however, there is lot more to focus on visual sentiment analysis using deep learning techniques. In our study, we aim to design a visual sentiment framework using a convolutional neural network. For experimentation, we employ the use of Flickr images for training purposes and Twitter images for testing purposes. The results depict that the proposed ‘visual sentiment framework using convolutional neural network’ shows improved performance for analyzing the sentiments associated with the images.

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Title: Image Sentiment Analysis Using Convolutional Neural Network
Authors: Akshi Kumar
Arunima Jaiswal
Publisher: Springer International Publishing
Book: Intelligent Systems Design and Applications
Print ISBN: 978-3-319-76347-7

Electronic ISBN: 978-3-319-76348-4

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-76348-4_45

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