Análise de redes sociais como estratégia de apoio à vigilância em saúde durante a Covid-19

ABSTRACT The large volume of data generated on social networks is used by companies to monitor public opinion about their products and services. These data may contain useful information for health surveillance, such as in assessing the impact of public policies or identifying fake news. This work presents results of studies that demonstrate how analysis of data from social networks may be applied to surveillance activities, using the covid-19 pandemic as a case study. An approach based on data science was used, with information extracted through machine learning algorithms. Results indicate that this approach can reveal useful information for surveillance activities, providing a real-time view of aspects related to the pandemic.

摘要：社交网络产生的海量数据被企业用于监测公众对其产品及服务的舆论态势。此类数据可应用于公共卫生监测领域，例如评估公共政策的实施影响或识别虚假新闻。本研究展示了相关研究成果，证明以新冠疫情（COVID-19 pandemic）为案例研究对象时，社交网络数据分析可如何应用于各类监测活动。本研究采用基于数据科学的分析方法，通过机器学习算法提取相关信息。研究结果表明，该方法能够为监测活动提供有效信息，可呈现与疫情相关各维度的实时视图。