Open Access
ARTICLE
Sentiment Analysis Using Deep Learning Approach
Peng Cen1, Kexin Zhang1, Desheng Zheng1, *
1 School of Computer Science, Research Center for Cyber Security, Southwest Petroleum University,
Chengdu, 610500, China.
* Corresponding Author: Desheng Zheng. Email: .
Journal on Artificial Intelligence 2020, 2(1), 17-27. https://doi.org/10.32604/jai.2020.010132
Received 13 February 2020; Accepted 01 April 2020; Issue published 15 July 2020
Abstract
Deep learning has made a great breakthrough in the field of speech and image
recognition. Mature deep learning neural network has completely changed the field of nat
ural language processing (NLP). Due to the enormous amount of data and opinions being
produced, shared and transferred everyday across the Internet and other media, sentiment
analysis has become one of the most active research fields in natural language processing.
This paper introduces three deep learning networks applied in IMDB movie reviews sent
iment analysis. Dataset was divided to 50% positive reviews and 50% negative reviews.
Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) neural networ
ks are two main types, which are widely used in NLP tasks, while Convolutional Neural
Networks (CNN) is often used in image recognition. The results have shown that, CNN n
etwork model can achieve good classification effect when applied to sentiment analysis o
f movie reviews. CNN have reported the accuracy of 88.22%, while RNN and LSTM hav
e reported accuracy of 68.64% and 85.32% respectively.
Keywords
Cite This Article
P. Cen, K. Zhang and D. Zheng, "Sentiment analysis using deep learning approach,"
Journal on Artificial Intelligence, vol. 2, no.1, pp. 17–27, 2020. https://doi.org/10.32604/jai.2020.010132
Citations