This paper is in the following e-collection/theme issue:

Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1015) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1573) Infodemiology and Infoveillance (1278) Mass Media/Social Media Communication and Campaigns (450)

Published on in Vol 2, No 2 (2016): Jul-Dec

Estimating the Duration of Public Concern After the Fukushima Dai-ichi Nuclear Power Station Accident From the Occurrence of Radiation Exposure-Related Terms on Twitter: A Retrospective Data Analysis

Estimating the Duration of Public Concern After the Fukushima Dai-ichi Nuclear Power Station Accident From the Occurrence of Radiation Exposure-Related Terms on Twitter: A Retrospective Data Analysis

Estimating the Duration of Public Concern After the Fukushima Dai-ichi Nuclear Power Station Accident From the Occurrence of Radiation Exposure-Related Terms on Twitter: A Retrospective Data Analysis

Authors of this article:

Naoki Nishimoto1 Author Orcid Image ;   Mizuki Ota2 Author Orcid Image ;   Ayako Yagahara3 Author Orcid Image ;   Katsuhiko Ogasawara4 Author Orcid Image
Article Authors Cited by (2) Tweetations (4) Metrics

Journals

  1. Yagahara A, Hanai K, Hasegawa S, Ogasawara K. Relationships Among Tweets Related to Radiation: Visualization Using Co-Occurring Networks. JMIR Public Health and Surveillance 2018;4(1):e26 View
  2. Lorenzoni V, Andreozzi G, Bazzani A, Casigliani V, Pirri S, Tavoschi L, Turchetti G. How Italy Tweeted about COVID-19: Detecting Reactions to the Pandemic from Social Media. International Journal of Environmental Research and Public Health 2022;19(13):7785 View