Addepalli Lavanya, Panwar Darsha, P. Akhil, Jaime Lloret, Navandar Yogeshwar
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引用次数: 0
摘要
使用不同交通方式的人类流动性不断增加。旅行时晒活动的文化在社交网络上引起了极大的关注。社交网络平台的发展使得全球用户数量成倍增长。这些在线平台创造的数据和信息的组合在数量和主题种类方面是巨大的。用户生产信息的实时存在激发了研究人员对材料进行分析,以获得对时事的实时洞察。重点是收集新冠肺炎疫情前100天实时旅行活动的推文,以中国机场为来源。本文阐述了covid-19从中国及东亚邻国到世界其他地区的实时传播的多维可视化。使用的可视化工具是python folium, matplotlib & networks/graphx, Carto, Tableau, Google Data Studio和MS Excel。
A Real-Time Human Mobility Visualization of Covid-19 Spread from East Asian Countries
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.