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

Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1139) Infodemiology and Infoveillance (1558)

Published on in Vol 4, No 1 (2018): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/7598, first published .
Relationships Among Tweets Related to Radiation: Visualization Using Co-Occurring Networks

Relationships Among Tweets Related to Radiation: Visualization Using Co-Occurring Networks

Relationships Among Tweets Related to Radiation: Visualization Using Co-Occurring Networks

Authors of this article:

Ayako Yagahara1, 2 Author Orcid Image ;   Keiri Hanai3 Author Orcid Image ;   Shin Hasegawa4, 5 Author Orcid Image ;   Katsuhiko Ogasawara2 Author Orcid Image
Article Authors Cited by (6) Tweetations (2) Metrics

Journals

  1. Ahmed W, Marin-Gomez X, Vidal-Alaball J. Contextualising the 2019 E-Cigarette Health Scare: Insights from Twitter. International Journal of Environmental Research and Public Health 2020;17(7):2236 View
  2. Hasegawa S, Suzuki T, Yagahara A, Kanda R, Aono T, Yajima K, Ogasawara K. Changing Emotions About Fukushima Related to the Fukushima Nuclear Power Station Accident—How Rumors Determined People’s Attitudes: Social Media Sentiment Analysis. Journal of Medical Internet Research 2020;22(9):e18662 View
  3. Zarrabeitia-Bilbao E, Jaca-Madariaga M, Rio-Belver R, Álvarez-Meaza I. Nuclear energy: Twitter data mining for social listening analysis. Social Network Analysis and Mining 2023;13(1) View
  4. Yagahara A, Tanikawa T, Fukuda A, Ando D, Suzuki T, Karata S, Uesugi M. Identification of problems in picture archiving and communication systems management using text mining. Health and Technology 2023;13(1):133 View
  5. Zhu Y, Jiang H, Duan Y. Cross-Cultural Communication Challenges in Global Environmental Issues: Multilingual Topic Modeling of the Fukushima Contaminated Water Discharge. Environmental Communication 2025:1 View
  6. Sun Y, Tsuruta H, Kumagai M, Kurosaki K. YouTube-based topic modeling and large language model sentiment analysis of Japanese online discourse on nuclear energy. Journal of Nuclear Science and Technology 2025;62(11):1038 View