Analysis of risk behavior-related Tweets
・Tweets related to actions of high infection risk were extracted and compared with positive COVID-19 cases. Tweets including the following keywords were subject to analysis:
-Drinking session, End-of-year Party, Christmas Party, New Year Party (Respectively 飲み会、忘年会、クリスマスパーティ、新年会 in Japanese)
-Karaoke (カラオケ in Japanese)
-Fitness center (ジム in Japanese)
-Hanami (“Flower-viewing”, 花見 in Japanese)
-Barbecue (バーベキュー in Japanese)
・The situations within Tokyo and Osaka regions were compared with each other, using location information from Twitter user profiles.
Summary
・The number of excursion-related tweets nationwide is increasing since December.
-Tweets related to drinking session and End-of-year party is continuing to increase; caution is advised.
-Tweets related to Karaoke was in an increase since December, but has shown a decrease last week (details below)
・Effects of news on the Omicron variant.
-On December 16th, the news of a close contact of the omicron variant going to a soccer stadium went viral on Twitter.
-Tweets related to drinking session increased compared to last week, but were in decrease compared to last week as of December 18th (Sat).
-Tweets related to End-of-year session increased compared to last week, but the rate of increase was lessened compared to last week as of December 18th (Sat).
-Tweets related to Karaoke decreased rapidly compared to last week; the shape of the peak changed as well.
As of December 19th, 2021
※ Blue sections indicate time periods of a state of emergency.
Based on Twitter data provided by NTT DATA.
As of December 29th, 2021
※ Blue sections indicate time periods of a state of emergency.
Based on Twitter data provided by NTT DATA.
As of December 29th, 2021
※ Blue sections indicate time periods of a state of emergency.
Based on Twitter data provided by NTT DATA.
As of December 29th, 2021
※ Blue sections indicate time periods of a state of emergency.
Based on Twitter data provided by NTT DATA.
As of December 29th, 2021
※ Blue sections indicate time periods of a state of emergency.
Based on Twitter data provided by NTT DATA.