SoBigDemicSys: A Social Media based Monitoring System for Emerging Pandemics with Big Data

Tung Khanh Tran, Xuan-Son Vu, Lili Jiang

Abstract: The outbreak of Covid-19 pandemic has caused millions of people infected and dead, resulting in global economy depression. Lessons learned to minimize the damage in an emerging pandemic is that timely tracking and reasonable trend prediction are required to help the society (e.g., municipality, institutions, and industries) with timely planning for efficient resource preparation and allocation. This paper presents a system to monitor the pandemic trends, analyze the correlation and impacts, predict the evolution, and visualize the prediction results to end users as social indicators. The significance lies in the fact that tracing online information collection for pandemic related prediction has less time lag, cheaper cost, and more potential information indicators. Demo video is available at https://vimeo.com/711930134.