基于土耳其每日Covid-19表的Twitter情绪分析

Buket Kaya, Abdullah Günay
{"title":"基于土耳其每日Covid-19表的Twitter情绪分析","authors":"Buket Kaya, Abdullah Günay","doi":"10.35377/saucis...932620","DOIUrl":null,"url":null,"abstract":"The coronavirus pandemic, which began to affect the whole world in early 2020, has become the most talked about agenda item by individuals. Individuals announce their feelings and thoughts through various communication channels and receive news from what is happening around them. One of the most important channels of communication is Twitter. Individuals express their feelings and thoughts by interacting with the tweets posted. This study aims to analyze the emotions of the comments made under the \"daily coronavirus table\" shared by the Republic of Turkey Ministry of Health and to measure their relationship with the daily number of cases and deaths. In the study, emotional classification of tweets was implemented using LSTM, GRU and BERT methods from deep learning algorithms. The results of all three algorithms were compared with the daily number of cases and deaths.","PeriodicalId":257636,"journal":{"name":"Sakarya University Journal of Computer and Information Sciences","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Twitter Sentiment Analysis Based on Daily Covid-19 Table in Turkey\",\"authors\":\"Buket Kaya, Abdullah Günay\",\"doi\":\"10.35377/saucis...932620\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The coronavirus pandemic, which began to affect the whole world in early 2020, has become the most talked about agenda item by individuals. Individuals announce their feelings and thoughts through various communication channels and receive news from what is happening around them. One of the most important channels of communication is Twitter. Individuals express their feelings and thoughts by interacting with the tweets posted. This study aims to analyze the emotions of the comments made under the \\\"daily coronavirus table\\\" shared by the Republic of Turkey Ministry of Health and to measure their relationship with the daily number of cases and deaths. In the study, emotional classification of tweets was implemented using LSTM, GRU and BERT methods from deep learning algorithms. The results of all three algorithms were compared with the daily number of cases and deaths.\",\"PeriodicalId\":257636,\"journal\":{\"name\":\"Sakarya University Journal of Computer and Information Sciences\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sakarya University Journal of Computer and Information Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.35377/saucis...932620\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sakarya University Journal of Computer and Information Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35377/saucis...932620","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

新冠肺炎疫情从2020年初开始影响全球,成为人们最关心的议题。个人通过各种沟通渠道表达自己的感受和想法,并从周围发生的事情中获得消息。最重要的沟通渠道之一是Twitter。个人通过与发布的推文互动来表达自己的感受和想法。本研究旨在分析土耳其共和国卫生部共享的“每日冠状病毒表”下评论的情绪,并衡量它们与每日病例数和死亡人数的关系。在本研究中,使用深度学习算法中的LSTM、GRU和BERT方法对推文进行情感分类。将所有三种算法的结果与每日病例数和死亡人数进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Twitter Sentiment Analysis Based on Daily Covid-19 Table in Turkey
The coronavirus pandemic, which began to affect the whole world in early 2020, has become the most talked about agenda item by individuals. Individuals announce their feelings and thoughts through various communication channels and receive news from what is happening around them. One of the most important channels of communication is Twitter. Individuals express their feelings and thoughts by interacting with the tweets posted. This study aims to analyze the emotions of the comments made under the "daily coronavirus table" shared by the Republic of Turkey Ministry of Health and to measure their relationship with the daily number of cases and deaths. In the study, emotional classification of tweets was implemented using LSTM, GRU and BERT methods from deep learning algorithms. The results of all three algorithms were compared with the daily number of cases and deaths.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信