Sentimental analysis using recurrent neural network

Author:

Thomas Merin,C.A Latha

Abstract

Sentiment analysis has been an important topic of discussion from two decades since Lee published his first paper on the sentimental analysis in 2002. Apart from the sentimental analysis in English, it has spread its wing to other natural languages whose significance is very important in a multi linguistic country like India. The traditional approaches in machine learning have paved better accuracy for the Analysis. Deep Learning approaches have gained its momentum in recent years in sentimental analysis. Deep learning mimics the human learning so expectations are to meet higher levels of accuracy. In this paper we have implemented sentimental analysis of tweets in South Indian language Malayalam. The model used is Recurrent Neural Networks Long Short-Term Memory, a deep learning technique to predict the sentiments analysis. Achieved accuracy was found increasing with quality and depth of the datasets. 

Publisher

Science Publishing Corporation

Subject

Hardware and Architecture,General Engineering,General Chemical Engineering,Environmental Engineering,Computer Science (miscellaneous),Biotechnology

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Comparative Study of Movie Review Segregation Using Sentiment Analysis;2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE);2024-02-22

2. Sentimental Analysis using Neural Network;International Journal of Advanced Research in Science, Communication and Technology;2023-11-20

3. Applying bag of words approach to determine remote sensing technology acceptance among smallholder plantations;Arab Gulf Journal of Scientific Research;2023-07-18

4. Evaluation and Analysis Data from Twitter Data By Using Hybrid CNN & LTSM;2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA);2023-06-08

5. Sentiment Analysis Dashboard for Socia Media comments using BERT;2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT);2023-05-05

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3