利用Twitter和Instagram数据分析印尼Covid-19大流行期间政府对开斋节返家的监管情绪

Tubagus Ahmad Marzuqi, Evelline Kristiani, I. Budi, A. Santoso, P. K. Putra
{"title":"利用Twitter和Instagram数据分析印尼Covid-19大流行期间政府对开斋节返家的监管情绪","authors":"Tubagus Ahmad Marzuqi, Evelline Kristiani, I. Budi, A. Santoso, P. K. Putra","doi":"10.1063/5.0107439","DOIUrl":null,"url":null,"abstract":"The Covid-19 pandemic has resulted in an often uncertain situation. On this basis, the government has implemented a ban on going home for the second time in 2021 to prevent a potential increase in Covid-19 cases. This rule raises pros and cons in society. Twitter and Instagram as social media platforms then became a means to voice reactions to the regulation, as well as opinions and criticisms The goal of this study is to find out how people feel about the situation the \"Prohibition of Homecoming in 2021\". The data mining approach is used in this study to classify public sentiments conveyed not only through the Twitter platform but also Instagram. The Naive Bayes and Decision Tree algorithms were used to create the classification model. On Twitter data 87.93% F1 score and 92.63% F1 Score on Instagram data. This study shows, the majority of people have negative sentiments about the \"Prohibition of Homecoming in 2021\"both on Twitter and Instagram platforms. © 2022 Author(s).","PeriodicalId":298649,"journal":{"name":"THE 2ND INTERNATIONAL CONFERENCE OF SCIENCE AND INFORMATION TECHNOLOGY IN SMART ADMINISTRATION (ICSINTESA 2021)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of government regulations sentiment regarding the Eid al-Fitr homecoming during Covid-19 pandemic in Indonesia using Twitter and Instagram data\",\"authors\":\"Tubagus Ahmad Marzuqi, Evelline Kristiani, I. Budi, A. Santoso, P. K. Putra\",\"doi\":\"10.1063/5.0107439\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Covid-19 pandemic has resulted in an often uncertain situation. On this basis, the government has implemented a ban on going home for the second time in 2021 to prevent a potential increase in Covid-19 cases. This rule raises pros and cons in society. Twitter and Instagram as social media platforms then became a means to voice reactions to the regulation, as well as opinions and criticisms The goal of this study is to find out how people feel about the situation the \\\"Prohibition of Homecoming in 2021\\\". The data mining approach is used in this study to classify public sentiments conveyed not only through the Twitter platform but also Instagram. The Naive Bayes and Decision Tree algorithms were used to create the classification model. On Twitter data 87.93% F1 score and 92.63% F1 Score on Instagram data. This study shows, the majority of people have negative sentiments about the \\\"Prohibition of Homecoming in 2021\\\"both on Twitter and Instagram platforms. © 2022 Author(s).\",\"PeriodicalId\":298649,\"journal\":{\"name\":\"THE 2ND INTERNATIONAL CONFERENCE OF SCIENCE AND INFORMATION TECHNOLOGY IN SMART ADMINISTRATION (ICSINTESA 2021)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"THE 2ND INTERNATIONAL CONFERENCE OF SCIENCE AND INFORMATION TECHNOLOGY IN SMART ADMINISTRATION (ICSINTESA 2021)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1063/5.0107439\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"THE 2ND INTERNATIONAL CONFERENCE OF SCIENCE AND INFORMATION TECHNOLOGY IN SMART ADMINISTRATION (ICSINTESA 2021)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1063/5.0107439","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

2019冠状病毒病大流行导致了一种往往不确定的局面。在此基础上,政府为防止新冠肺炎病例增加,在2021年实施了第二次禁止回国措施。这条规则在社会上引起了赞成和反对。Twitter和Instagram作为社交媒体平台,随后成为表达对该规定的反应,以及意见和批评的手段。本研究的目的是了解人们对“2021年禁止返乡”的情况的感受。本研究使用数据挖掘方法对通过Twitter平台和Instagram传达的公众情绪进行分类。采用朴素贝叶斯和决策树算法建立分类模型。在Twitter数据上F1得分87.93%,在Instagram数据上F1得分92.63%。这项研究显示,在推特和Instagram平台上,大多数人对“2021年禁止返乡”持负面情绪。©2022作者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of government regulations sentiment regarding the Eid al-Fitr homecoming during Covid-19 pandemic in Indonesia using Twitter and Instagram data
The Covid-19 pandemic has resulted in an often uncertain situation. On this basis, the government has implemented a ban on going home for the second time in 2021 to prevent a potential increase in Covid-19 cases. This rule raises pros and cons in society. Twitter and Instagram as social media platforms then became a means to voice reactions to the regulation, as well as opinions and criticisms The goal of this study is to find out how people feel about the situation the "Prohibition of Homecoming in 2021". The data mining approach is used in this study to classify public sentiments conveyed not only through the Twitter platform but also Instagram. The Naive Bayes and Decision Tree algorithms were used to create the classification model. On Twitter data 87.93% F1 score and 92.63% F1 Score on Instagram data. This study shows, the majority of people have negative sentiments about the "Prohibition of Homecoming in 2021"both on Twitter and Instagram platforms. © 2022 Author(s).
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