ABSTRACT
Human mobility using different modes of transportation is constantly increasing. The culture of posting activities while travelling has gained attention on social networks immensely. The evolution of social networking platforms has resulted in an engaging user base multiplying across the globe. The combination of data and information created by these online platforms is massive in terms of the volume and variety of topics. The real-time existence of user-produced information has inspired researchers to analyze material to obtain real-time insight into current affairs. The focus is on collecting tweets of real-time travelling activities for the first 100 days of Covid-19 keeping Chinese Airports as the source. This paper illustrates the multidimensional visualization of real-time covid-19 spread from China neighbouring East Asian countries to the rest of the world. The visualization tools used are python folium, matplotlib networks/graphx, Carto, Tableau, Google Data Studio, and MS Excel. © 2021 IEEE.