Abstract: Emotional geography research has complex geospatial patterns, complex temporal processesand complex characteristics of time and space. We obtained big data on Weibo through the web crawler.Based on emotional identification and with network attention as the entry point, we utilized Gephi cluste.ring, visualization and sentiment analysis to analyze the text word frequency, semantic network, emotion.etc. , and focused on analyzing the temporal and spatial characteristics of the Wuhan epidemic, networkattention and emotional identification. The research showed that: 1) The Wuhan epidemic showstemporalchanges and spatial characteristics of decreasing from the center to the surroundings; 2 ) The network attention to Wuhan's epidemic in China showsregional differences, “ convex” temporal changes and groupdifferences, and was mainly dominatd by positive emotional identification; 3) The emotional identification vary with the Wuhan epidemic during the period of “early-mid-post”, showing the temporal patternof “ universal emotional identification-positive emotional identification-social emotional identification” andthe same inter-provincial differences as network attention. Counterpart assistance to Wuhan was the main factor to mobilize social emotional identification.

Key words: temporal and spatial characteristics, emotional geography, emotional identification, COVlD.19 epidemic in Wuhan, network attention