An Efficient Approach for Sentiment Analysis using Convolutional Neural Network

Alpna Patel, Arvind Kumar Tiwari, S. S. Ahmad

2021

Abstract

Sentiment analysis is a substantial area of research nowadays. Many researchers have proved the subject in recent years. The reason behind that is the rapidly growing opinionated data on social media. With the aim of surmounting this obstacle, we introduce an efficient approach for sentiment analysis that ensemble the advantages of two deep learning models. Sentiment mining is the process of extracting opinion, feelings, emotions and attitude towards a specific task. Here, we have collected the IMDB movie review dataset as well as used two kind of deep learning classifiers to analyze the experimental result. Hence, the contemplated models are Long Short Term Memory and Convolutional Neural Network.. The efficiency of the proposed model is compared with other traditional approaches in experimental work and outcome of the result shows that the ensemble approach can effectively improve the accuracy to predict the sentiments.

Paper Citation

in Harvard Style

Patel A., Tiwari A. and Ahmad S. (2021). An Efficient Approach for Sentiment Analysis using Convolutional Neural Network. In Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE, ISBN 978-989-758-544-9, pages 12-21. DOI: 10.5220/0010561700003161

in Bibtex Style

@conference{icacse21,
author={Alpna Patel and Arvind Kumar Tiwari and S. S. Ahmad},
title={An Efficient Approach for Sentiment Analysis using Convolutional Neural Network},
booktitle={Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE,},
year={2021},
pages={12-21},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010561700003161},
isbn={978-989-758-544-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE,
TI - An Efficient Approach for Sentiment Analysis using Convolutional Neural Network
SN - 978-989-758-544-9
AU - Patel A.
AU - Tiwari A.
AU - Ahmad S.
PY - 2021
SP - 12
EP - 21
DO - 10.5220/0010561700003161