• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

巴西的 COVID-19 信息疫情:谷歌搜索数据趋势。

The COVID-19 infodemic in Brazil: trends in Google search data.

机构信息

Institute of Technology, Federal University of Pará, Belém, Pará, Brazil.

University of Amazon, Belém, Pará, Brazil.

出版信息

PeerJ. 2022 Aug 4;10:e13747. doi: 10.7717/peerj.13747. eCollection 2022.

DOI:10.7717/peerj.13747
PMID:35945937
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9357377/
Abstract

BACKGROUND

Since the beginning of the new coronavirus pandemic, there has been much information about the disease and the virus has been in the spotlight, shared and commented upon on the Internet. However, much of this information is infodemics and can interfere with the advancement of the disease and that way that populations act. Thus, Brazil is a country that requires attention, as despite the fact that in almost two years of pandemic it has shown a devastating numbers of deaths and number of cases, and generates false, distorted and malicious news about the pandemic. This work intends to understand the attitudes of the Brazilian population using infodemic queries from the Google Trends search tool and social and income variables.

METHODS

Data from infodemic research carried out on Google Trends, between January 1, 2020 and June 30, 2021, with socioeconomic data, such as income and education, were unified in a single database: standardization and exploratory and multivalued techniques based on grouping were used in the study.

RESULTS

In the analysis of the search trend of infodemic terms, it is clear that the categories of Prevention and Beliefs should stand out in Brazil, where there is a diverse culture. It is followed by the COVID-19 Treatment category, with treatments that were not those recommended by the authorities. Income transfer programs and information on socioeconomic variables did not have much impact on infodemic surveys, but it was observed that states where President Bolsonaro has more supporters had researched more infodemic information.

CONCLUSIONS

In a country as geographically large as Brazil, it is important that political authorities go to great lengths to disseminate reliable information and monitor the infodemic in the media and on the internet. It was concluded that the denial of the pandemic and the influence of political leaders influenced the search for infodemic information, contributing to a disorganization in the control of the disease and prevention measures.

摘要

背景

自新冠疫情开始以来,有关该疾病的信息很多,病毒也成为焦点,在互联网上被分享和评论。然而,这些信息中很多都是信息疫情,可能会干扰疾病的进展和人群的行为方式。因此,巴西是一个需要关注的国家,因为尽管在将近两年的大流行中,它的死亡人数和病例数都令人震惊,但它还制造了有关大流行的虚假、扭曲和恶意新闻。这项工作旨在通过 Google Trends 搜索工具中的信息疫情查询以及社会和收入变量来了解巴西民众的态度。

方法

对 2020 年 1 月 1 日至 2021 年 6 月 30 日期间在 Google Trends 上进行的信息疫情研究的数据,与收入和教育等社会经济数据统一在一个单一的数据库中:使用基于标准化和探索性以及基于分组的多值技术进行了研究。

结果

在信息疫情术语搜索趋势的分析中,巴西的预防和信仰类别应该突出,因为巴西的文化是多样化的。其次是 COVID-19 治疗类别,其中的治疗方法并不是当局推荐的。收入转移计划和社会经济变量的信息对信息疫情调查没有太大影响,但观察到博索纳罗总统支持者较多的州对信息疫情的研究更多。

结论

在像巴西这样幅员辽阔的国家,政治当局应该不遗余力地传播可靠的信息,并监测媒体和互联网上的信息疫情。结论是,对大流行的否认和政治领导人的影响影响了对信息疫情的搜索,导致疾病控制和预防措施的混乱。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/41d519b0c551/peerj-10-13747-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/d9f44008a225/peerj-10-13747-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/004e3df7f020/peerj-10-13747-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/81d0cb89255d/peerj-10-13747-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/229df6ba9ca2/peerj-10-13747-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/3d473f008d29/peerj-10-13747-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/ad9eda16f852/peerj-10-13747-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/ba981b90f774/peerj-10-13747-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/41d519b0c551/peerj-10-13747-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/d9f44008a225/peerj-10-13747-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/004e3df7f020/peerj-10-13747-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/81d0cb89255d/peerj-10-13747-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/229df6ba9ca2/peerj-10-13747-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/3d473f008d29/peerj-10-13747-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/ad9eda16f852/peerj-10-13747-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/ba981b90f774/peerj-10-13747-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c35b/9357377/41d519b0c551/peerj-10-13747-g008.jpg

相似文献

1
The COVID-19 infodemic in Brazil: trends in Google search data.巴西的 COVID-19 信息疫情:谷歌搜索数据趋势。
PeerJ. 2022 Aug 4;10:e13747. doi: 10.7717/peerj.13747. eCollection 2022.
2
An Analysis of the Deleterious Impact of the Infodemic during the COVID-19 Pandemic in Brazil: A Case Study Considering Possible Correlations with Socioeconomic Aspects of Brazilian Demography.巴西新冠疫情期间信息疫情的有害影响分析:一项考虑与巴西人口社会经济方面可能存在相关性的案例研究。
Int J Environ Res Public Health. 2022 Mar 9;19(6):3208. doi: 10.3390/ijerph19063208.
3
Global Infodemiology of COVID-19: Analysis of Google Web Searches and Instagram Hashtags.新型冠状病毒肺炎的全球信息流行病学:谷歌网络搜索和照片墙主题标签分析
J Med Internet Res. 2020 Aug 25;22(8):e20673. doi: 10.2196/20673.
4
COVID-19-Related Web Search Behaviors and Infodemic Attitudes in Italy: Infodemiological Study.意大利与 COVID-19 相关的网络搜索行为和信息疫情态度:信息疫情研究。
JMIR Public Health Surveill. 2020 May 5;6(2):e19374. doi: 10.2196/19374.
5
Understanding Health Communication Through Google Trends and News Coverage for COVID-19: Multinational Study in Eight Countries.通过谷歌趋势和新冠疫情新闻报道理解健康传播:八国跨国研究。
JMIR Public Health Surveill. 2021 Dec 21;7(12):e26644. doi: 10.2196/26644.
6
One Year of Coronavirus Disease 2019 (COVID-19) in Brazil: A Political and Social Overview.巴西的 2019 冠状病毒病(COVID-19)一年:政治和社会概述。
Ann Glob Health. 2021 May 18;87(1):44. doi: 10.5334/aogh.3182.
7
A new infodemiological approach through Google Trends: longitudinal analysis of COVID-19 scientific and infodemic names in Italy.一种新的通过谷歌趋势进行的信息流行病学方法:意大利 COVID-19 科学和信息疫情名称的纵向分析。
BMC Med Res Methodol. 2022 Jan 30;22(1):33. doi: 10.1186/s12874-022-01523-x.
8
Information-Seeking Patterns During the COVID-19 Pandemic Across the United States: Longitudinal Analysis of Google Trends Data.美国新冠疫情期间的信息寻求模式:谷歌趋势数据的纵向分析
J Med Internet Res. 2021 May 3;23(5):e22933. doi: 10.2196/22933.
9
Online Information of COVID-19: Visibility and Characterization of Highest Positioned Websites by Google between March and April 2020-A Cross-Country Analysis.2020 年 3 月至 4 月期间谷歌对 COVID-19 最高排名网站的在线信息:可见性和特征分析——一项跨国研究
Int J Environ Res Public Health. 2022 Jan 28;19(3):1491. doi: 10.3390/ijerph19031491.
10
Impact of 'infodemic in pandemic' on food and nutrition related perceptions and practices of Indian internet users.大流行期间“信息疫情”对印度互联网用户有关食物和营养的认知与实践的影响。
PLoS One. 2022 Apr 21;17(4):e0266705. doi: 10.1371/journal.pone.0266705. eCollection 2022.

引用本文的文献

1
Efficacy of Ivermectin, Chloroquine/Hydroxychloroquine, and Azithromycin in Managing COVID-19: A Systematic Review of Phase III Clinical Trials.伊维菌素、氯喹/羟氯喹及阿奇霉素治疗新冠肺炎的疗效:III期临床试验的系统评价
Biomedicines. 2024 Sep 27;12(10):2206. doi: 10.3390/biomedicines12102206.
2
Inefficacious drugs against covid-19: analysis of sales, tweets, and search engines.针对 COVID-19 的无效药物:销售、推文和搜索引擎分析。
Rev Saude Publica. 2024 Feb 26;58:06. doi: 10.11606/s1518-8787.2024058005413. eCollection 2024.

本文引用的文献

1
A new infodemiological approach through Google Trends: longitudinal analysis of COVID-19 scientific and infodemic names in Italy.一种新的通过谷歌趋势进行的信息流行病学方法:意大利 COVID-19 科学和信息疫情名称的纵向分析。
BMC Med Res Methodol. 2022 Jan 30;22(1):33. doi: 10.1186/s12874-022-01523-x.
2
The COVID-19 Infodemic: Infodemiology Study Analyzing Stigmatizing Search Terms.新冠疫情信息疫情:分析污名化搜索词的信息流行病学研究
J Med Internet Res. 2020 Nov 16;22(11):e22639. doi: 10.2196/22639.
3
Global Infodemiology of COVID-19: Analysis of Google Web Searches and Instagram Hashtags.
新型冠状病毒肺炎的全球信息流行病学:谷歌网络搜索和照片墙主题标签分析
J Med Internet Res. 2020 Aug 25;22(8):e20673. doi: 10.2196/20673.
4
COVID-19 Mortality Underreporting in Brazil: Analysis of Data From Government Internet Portals.巴西新冠病毒疾病(COVID-19)死亡人数漏报情况:来自政府互联网门户网站的数据分析
J Med Internet Res. 2020 Aug 18;22(8):e21413. doi: 10.2196/21413.
5
Social distancing measures to control the COVID-19 pandemic: potential impacts and challenges in Brazil.控制新冠疫情的社交距离措施:在巴西的潜在影响和挑战
Cien Saude Colet. 2020 Jun;25(suppl 1):2423-2446. doi: 10.1590/1413-81232020256.1.10502020. Epub 2020 Apr 22.
6
COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data.新冠疫情与5G阴谋论:基于推特数据的社交网络分析
J Med Internet Res. 2020 May 6;22(5):e19458. doi: 10.2196/19458.
7
Creating COVID-19 Stigma by Referencing the Novel Coronavirus as the "Chinese virus" on Twitter: Quantitative Analysis of Social Media Data.在推特上将新型冠状病毒称为“中国病毒”从而制造新冠病毒污名化:社交媒体数据的定量分析
J Med Internet Res. 2020 May 6;22(5):e19301. doi: 10.2196/19301.
8
COVID-19-Related Web Search Behaviors and Infodemic Attitudes in Italy: Infodemiological Study.意大利与 COVID-19 相关的网络搜索行为和信息疫情态度:信息疫情研究。
JMIR Public Health Surveill. 2020 May 5;6(2):e19374. doi: 10.2196/19374.
9
Coronavirus Goes Viral: Quantifying the COVID-19 Misinformation Epidemic on Twitter.冠状病毒迅速传播:量化推特上关于新冠疫情的错误信息传播情况
Cureus. 2020 Mar 13;12(3):e7255. doi: 10.7759/cureus.7255.
10
Assessment of Health Information About COVID-19 Prevention on the Internet: Infodemiological Study.评估互联网上关于 COVID-19 预防的健康信息:信息流行病学研究。
JMIR Public Health Surveill. 2020 Apr 1;6(2):e18717. doi: 10.2196/18717.