论文标题
COVID-19-ENMOTION监测是增加发展地区疾病暴发的准备的工具
COVID-19 Emotion Monitoring as a Tool to Increase Preparedness for Disease Outbreaks in Developing Regions
论文作者
论文摘要
共同19-19大流行带来了许多挑战，从医院占领管理到锁定的心理健康，例如焦虑或抑郁。在这项工作中，我们通过基于最先进的自然语言处理模型来开发Twitter情感监测系统来为后来的问题提供解决方案。该系统在城市的帐户以及政治家和健康权限的Twitter帐户上监视六种不同的情绪。通过匿名使用情感监测仪，卫生当局和私人健康保险公司可以制定策略来解决自杀和临床抑郁症等问题。为此任务选择的模型是从西班牙语料库（Beto）预先训练的变压器（BERT）的双向编码器表示。该模型在验证数据集上表现良好。该系统是在线部署的，作为Web应用程序的一部分，用于哥伦比亚的COVID-19，可在https://epidemiologia-matematica.org上获得。
The COVID-19 pandemic brought many challenges, from hospital-occupation management to lock-down mental-health repercussions such as anxiety or depression. In this work, we present a solution for the later problem by developing a Twitter emotion-monitor system based on a state-of-the-art natural-language processing model. The system monitors six different emotions on accounts in cities, as well as politicians and health-authorities Twitter accounts. With an anonymous use of the emotion monitor, health authorities and private health-insurance companies can develop strategies to tackle problems such as suicide and clinical depression. The model chosen for such a task is a Bidirectional-Encoder Representations from Transformers (BERT) pre-trained on a Spanish corpus (BETO). The model performed well on a validation dataset. The system is deployed online as part of a web application for simulation and data analysis of COVID-19, in Colombia, available at https://epidemiologia-matematica.org.
