Noise-Regularized Bidirectional Gated Recurrent Unit With Self-Attention Layer for Text and Emoticon Classification
Author:
Affiliation:
1. Visvesvaraya Technological University, India
2. City Engineering College, Bangalore, India
Abstract
The emoji are capable of expressing emotion beyond the meaning of the text by displaying visual emotions, which makes the content more distinct. Recently, emoji and text prediction has gained more significance, since it is hard to choose the appropriate one from thousands of emoji candidates. The small-sized dataset provides a poor description of features that resulted in classification and showed overfitting and underfitting problems. Therefore, Noise Regularized Bidirectional Gated Recurrent Unit (Bi-GRU) with Self-Attention Layer (SAL) is proposed for the classification of text and emoji. The proposed Noise Regularized Bi-GRU which is an aspect-based sentiment analysis performs a series of experiments on Twitter data to predict the sentiment of a tweet. The proposed Noise Regularized BGRU with SAL method obtained an accuracy of 87.77 % better when compared to the deep learning model that obtained an accuracy of 86.27 %.
Publisher
IGI Global
Subject
Computer Networks and Communications,Computer Science Applications
Reference21 articles.
1. Sentiment Analysis of Covid-19 Tweets Using Evolutionary Classification-Based LSTM Model
2. An efficient hybrid filter and evolutionary wrapper approach for sentiment analysis of various topics on Twitter
3. Cross-Cultural Polarity and Emotion Detection Using Sentiment Analysis and Deep Learning on COVID-19 Related Tweets
4. A Review: Machine Learning based Chronic Kidney Disease Prediction.;M.Jayashree;Sambodhi,2020
5. Hybrid context enriched deep learning model for fine-grained sentiment analysis in textual and visual semiotic modality social data
Cited by 1 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. DCCWOA: A multi-heuristic fault tolerant scheduling technique for cloud computing environment;Peer-to-Peer Networking and Applications;2023-01-12
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