{"uid": "COVID-19_a", "time_update": 1585306607, "title": "Temporal Analysis of COVID-19-related Weibo", "cnt_html": "
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Figure 1. The seasonal trend decomposition of the temporal trends of COVID-19-related Weibo. (a) Original temporal series; (b) seasonal component; (c) seasonally adjusted time series; (d) trend component.
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The results of the time series analysis of COVID-19-related Weibo texts are shown in \nFigure 1. Split by day, Figure 1a shows that the lowest point of the Weibo number on \nthe curve for each day appeared at 04:00, after which the curve began to rise sharply.\nFigure 1b shows the lowest point of cyclical change occurring at 06:00 every day, with\ntwo daily peaks around 11:00 and 23:00. Figure 1c shows the seasonally adjusted time \nseries, which shows the trend of the number of COVID-19-related Weibo after eliminating \nthe seasonal factor. Figure 1d shows the trend component reflecting the trends of the \nnumber of COVID-19 related Weibo. After COVID-19 occurred, a slight increase appeared \nfor a short time, then the amount increased sharply on January 20. The fluctuation reached \na peak on January 21, and then began to decrease but fluctuated until January 29. The\ncurve rose obviously on January 31 and reached a peak on February 1. It then steadily \nfluctuated from February 2 to 5, started to climb on February 6, and then steadily declined \nafter reaching the highest peak on February 7.

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