Harb Maria da Penha de Andrade Abi, Silva Lena Veiga E, Vijaykumar Nandamudi Lankalapalli, Silva Marcelino Silva da, Francês Carlos Renato Lisboa
Institute of Technology, Federal University of Para, Belem 66075-110, Brazil.
Center for Exact Sciences and Technology, University of Amazon, Belem 66060-902, Brazil.
Int J Environ Res Public Health. 2022 Mar 9;19(6):3208. doi: 10.3390/ijerph19063208.
Due to COVID-19, a huge amount of incorrect information has been disseminated on the internet, which may interfere with the disease's advance. This study analyzes the behavior of the Brazilian population during the pandemic, employing queries of infodemic data searched on Google Trends and relating them to socioeconomic and political indicators in the country. The z-score technique was used to standardize the data; and for multivalued analysis, dendrograms and the Elbow method detected similar patterns among Brazilian states. The result was divided into three analyses. In the analysis of the research trend of infodemic terms, the themes "Prevention and Beliefs" and "Treatment" prevailed. In the exploratory analysis, socioeconomic indicators related to income and education, as well as government programs, showed no impact on infodemic searches; but the results suggest that the states that supported the Brazilian president in the 2018 election, where he obtained more than 50% of the votes, were the states that most searched for infodemic terms: a total of 46.58% more infodemic searches than in the other states. In the multivalued analysis, the socioeconomic indicators used showed similarities in the patterns, highlighting a cluster containing 77% of all Brazilian states. The study concludes that denial about the pandemic and the influence of political leadership can influence infodemic information searches, contributing to a disorganization in the control of disease control and prevention measures.
由于新冠疫情，互联网上传播了大量错误信息，这可能会干扰疾病的防控进程。本研究分析了巴西民众在疫情期间的行为，利用在谷歌趋势上搜索到的信息疫情数据查询，并将其与该国的社会经济和政治指标相关联。采用z分数技术对数据进行标准化处理；对于多值分析，通过树状图和肘部方法在巴西各州中检测到相似模式。结果分为三项分析。在信息疫情术语研究趋势分析中，“预防与信念”和“治疗”主题占主导。在探索性分析中，与收入和教育相关的社会经济指标以及政府项目对信息疫情搜索没有影响；但结果表明，在2018年选举中支持巴西总统且他获得超过50%选票的州，是信息疫情术语搜索量最高的州：比其他州的信息疫情搜索总量多46.58%。在多值分析中，所使用的社会经济指标在模式上显示出相似性，突出了一个包含所有巴西州77%的集群。该研究得出结论，对疫情的否认以及政治领导力的影响会影响信息疫情信息搜索，导致疾病控制和预防措施管控的混乱。
