论文标题
Covidsens：关于Covid-19的可靠社会感知的愿景
CovidSens: A Vision on Reliable Social Sensing for COVID-19
论文作者
论文摘要
随着2019年冠状病毒病（Covid-19）的螺旋螺旋式大流行，它对传播有关该疾病的准确和及时信息的固有重要意义变得始终是重要的。由于互联网连接性和智能设备的无处不在，社交传感正在成为一种动态的AI驱动传感范式，以从在线用户中提取实时观察。在本文中，我们提出了Covidsens，这是基于社会传感的风险警报系统的愿景，以自发获取和分析社交数据以推断Covid-19-19。 Covidsens可以积极帮助使公众了解Covid-19-19，并确定容易发生风险的领域。 Covidsens的概念是由三个观察结果激励的：1）人们通过在线社交媒体积极分享他们在COVID-19的经验，2）官方警告渠道和新闻机构的速度比在社交媒体上报告的人相对较慢，而3）在线用户经常配备强大的移动设备，可以执行数据处理和分析。我们设想了前所未有的机会，可以利用普通人产生的帖子来建立实时传感和分析系统，用于收集和循环-19传播数据。具体而言，Covidsens的愿景试图回答以下问题：如何用谣言和错误信息提取有关Covid-19的可靠信息？如何及时有效地告知普通公众差异的状态？如何利用边缘设备上的计算能力来构建完全集成的基于边缘的社交传感平台？在本愿景论文中，我们讨论了共同体的作用，并确定了在开发可靠的基于社会传感的风险警报系统中的潜在挑战。我们设想，源自多个学科的方法可以有效解决挑战。最后，我们概述了Covidsens未来工作的一些研究指示。
With the spiraling pandemic of the Coronavirus Disease 2019 (COVID-19), it has becoming inherently important to disseminate accurate and timely information about the disease. Due to the ubiquity of Internet connectivity and smart devices, social sensing is emerging as a dynamic AI-driven sensing paradigm to extract real-time observations from online users. In this paper, we propose CovidSens, a vision of social sensing based risk alert systems to spontaneously obtain and analyze social data to infer COVID-19 propagation. CovidSens can actively help to keep the general public informed about the COVID-19 spread and identify risk-prone areas. The CovidSens concept is motivated by three observations: 1) people actively share their experience of COVID-19 via online social media, 2) official warning channels and news agencies are relatively slower than people reporting on social media, and 3) online users are frequently equipped with powerful mobile devices that can perform data processing and analytics. We envision unprecedented opportunities to leverage posts generated by ordinary people to build real-time sensing and analytic system for gathering and circulating COVID-19 propagation data. Specifically, the vision of CovidSens attempts to answer the questions: How to distill reliable information on COVID-19 with prevailing rumors and misinformation? How to inform the general public about the state of the spread timely and effectively? How to leverage the computational power on edge devices to construct fully integrated edge-based social sensing platforms? In this vision paper, we discuss the roles of CovidSens and identify potential challenges in developing reliable social sensing based risk alert systems. We envision that approaches originating from multiple disciplines can be effective in addressing the challenges. Finally, we outline a few research directions for future work in CovidSens.
