Analysis of the Regionality of the Number of Tweets Related to the 2011 Fukushima Nuclear Power Station Disaster: Content Analysis

被引:6
|
作者
Aoki, Tomohiro [1 ]
Suzuki, Teppei [2 ]
Yagahara, Ayako [3 ]
Hasegawa, Shin [1 ]
Tsuji, Shintaro [2 ]
Ogasawara, Katsuhiko [2 ]
机构
[1] Hokkaido Univ, Grad Sch Hlth Sci, Sapporo, Hokkaido, Japan
[2] Hokkaido Univ, Fac Hlth Sci, Sapporo, Hokkaido, Japan
[3] Hokkaido Univ Sci, Dept Radiol Technol, Sapporo, Hokkaido, Japan
来源
JMIR PUBLIC HEALTH AND SURVEILLANCE | 2018年 / 4卷 / 04期
关键词
Fukushima nuclear disaster; Twitter messaging; radiation; radioactivity; radioactive hazard release; geographic location; information dissemination; SOCIAL MEDIA; RISK;
D O I
10.2196/publichealth.7496
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: The Great East Japan Earthquake on March 11, 2011, triggered a huge tsunami, causing the Fukushima Daiichi nuclear disaster. Radioactive substances were carried in all directions, along with the risks of radioactive contamination. Mass media companies, such as television stations and news websites, extensively reported on radiological information related to the disaster. Upon digesting the available radiological information, many citizens turned to social media, such as Twitter and Facebook, to express their opinions and feelings. Thus, the Fukushima Daiichi nuclear disaster also changed the social media landscape in Japan. However, few studies have explored how the people in Japan who received information on radiation propagated the information. Objective: This study aimed to reveal how the number of tweets by citizens containing radiological information changed regionally on Twitter. Methods: The research used about 19 million tweets that included the terms "radiation," "radioactivity," and "radioactive substance" posted for 1 year after the Fukushima Daiichi nuclear disaster. Nearly 45,000 tweets were extracted based on their inclusion of geographic information (latitude and longitude). The number of monthly tweets in 4 districts (Fukushima Prefecture, prefectures around Fukushima Prefecture, within the Tokyo Electric Power Company area, and others) were analyzed. Results: The number of tweets containing the keywords per 100,000 people at the time of the casualty outbreak was 7.05 per month in Fukushima Prefecture, 2.07 per month in prefectures around Fukushima Prefecture, 5.23 per month in the area within Tokyo Electric Power Company, and 1.35 per month in others. The number of tweets per 100,000 people more than doubled in Fukushima Prefecture 2 months after the Fukushima Daiichi nuclear disaster, whereas the number decreased to around 0.7 similar to 0.8 tweets in other districts. Conclusions: The number of tweets per 100,000 people became half of that on March 2011 3 or 4 months after the Fukushima Daiichi Nuclear Plant disaster in 3 districts except district 1 (Fukushima Prefecture); the number became a half in Fukushima Prefecture half a year later.
引用
收藏
页码:95 / 105
页数:11
相关论文
共 33 条
  • [1] YouTube Videos Related to the Fukushima Nuclear Disaster: Content Analysis
    Cui, Limeng
    Chu, Lijuan
    JMIR PUBLIC HEALTH AND SURVEILLANCE, 2021, 7 (06):
  • [2] Changing Emotions About Fukushima Related to the Fukushima Nuclear Power Station Accident-How Rumors Determined People's Attitudes: Social Media Sentiment Analysis
    Hasegawa, Shin
    Suzuki, Teppei
    Yagahara, Ayako
    Kanda, Reiko
    Aono, Tatsuo
    Yajima, Kazuaki
    Ogasawara, Katsuhiko
    JOURNAL OF MEDICAL INTERNET RESEARCH, 2020, 22 (09)
  • [3] Mental health and disaster related attitudes among Japanese after the 2011 Fukushima nuclear disaster
    Palgi, Yuval
    Ben-Ezra, Menachem
    Aviel, Or
    Dubiner, Yonit
    Baruch, Evelyn
    Soffer, Yechiel
    Shrira, Amit
    JOURNAL OF PSYCHIATRIC RESEARCH, 2012, 46 (05) : 688 - 690
  • [4] Fukushima Mothers' Concerns and Associated Factors After the Fukushima Nuclear Power Plant Disaster: Analysis of Qualitative Data From the Fukushima Health Management Survey, 2011 to 2013
    Ito, Shinya
    Goto, Aya
    Ishii, Kayoko
    Ota, Misao
    Yasumura, Seiji
    Fujimori, Keiya
    ASIA-PACIFIC JOURNAL OF PUBLIC HEALTH, 2017, 29 : 151S - 160S
  • [5] A content analysis of depression-related tweets
    Cavazos-Rehg, Patricia A.
    Krauss, Melissa J.
    Sowles, Shaina
    Connolly, Sarah
    Rosas, Carlos
    Bharadwaj, Meghana
    Bierut, Laura J.
    COMPUTERS IN HUMAN BEHAVIOR, 2016, 54 : 351 - 357
  • [6] Nuclear power in Australia: A comparative analysis of public opinion regarding climate change and the Fukushima disaster
    Bird, Deanne K.
    Haynes, Katharine
    van den Honert, Rob
    McAneney, John
    Poortinga, Wouter
    ENERGY POLICY, 2014, 65 : 644 - 653
  • [7] People power: a content analysis of #VAWG tweets in India
    Iyengar, Jayanthi
    Upadhyay, Ashwani Kumar
    COGENT SOCIAL SCIENCES, 2024, 10 (01):
  • [8] fukushima Five Years On: A Multimethod Analysis of Twitter on the Anniversary of the Nuclear Disaster
    Rantasila, Anna
    Sirola, Anu
    Kekkonen, Arto
    Valaskivi, Katja
    Kunelius, Risto
    INTERNATIONAL JOURNAL OF COMMUNICATION, 2018, 12 : 928 - 949
  • [9] Symposium on disaster-related deaths after the Fukushima Daiichi Nuclear Power Plant accident
    Tsuboi, Motohiro
    Tani, Yuta
    Sawano, Toyoaki
    Ozaki, Akihiko
    Nonaka, Saori
    Zhao, Tianchen
    Hori, Arinobu
    Akihiro, Uto
    Zaima, Fumiyasu
    Watanabe, Toshihiko
    Tsubokura, Masaharu
    JOURNAL OF RADIOLOGICAL PROTECTION, 2022, 42 (03)
  • [10] Microbiome analysis of the restricted bacteria in radioactive element-containing water at the Fukushima Daiichi Nuclear Power Station
    Warashina, Tomoro
    Sato, Asako
    Hinai, Hiroshi
    Shaikhutdinov, Nurislam
    Shagimardanova, Elena
    Mori, Hiroshi
    Tamaki, Satoshi
    Saito, Motofumi
    Sanada, Yukihisa
    Sasaki, Yoshito
    Shimada, Kozue
    Dotsuta, Yuma
    Kitagaki, Toru
    Maruyama, Shigenori
    Gusev, Oleg
    Narumi, Issay
    Kurokawa, Ken
    Morita, Teppei
    Ebisuzaki, Toshikazu
    Nishimura, Akihiko
    Koma, Yoshikazu
    Kanai, Akio
    APPLIED AND ENVIRONMENTAL MICROBIOLOGY, 2024, 90 (04)