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Changing Emotions About Fukushima Related to the Fukushima Nuclear Power Station Accident-How Rumors Determined People's Attitudes : Social Media Sentiment Analysis
- Source :
- Journal of Medical Internet Research, Vol 22, Iss 9, p e18662 (2020), Journal of Medical Internet Research
- Publication Year :
- 2020
- Publisher :
- JMIR Publications, 2020.
-
Abstract
- Background Public interest in radiation rose after the Tokyo Electric Power Company (TEPCO) Fukushima Daiichi Nuclear Power Station accident was caused by an earthquake off the Pacific coast of Tohoku on March 11, 2011. Various reports on the accident and radiation were spread by the mass media, and people displayed their emotional reactions, which were thought to be related to information about the Fukushima accident, on Twitter, Facebook, and other social networking sites. Fears about radiation were spread as well, leading to harmful rumors about Fukushima and the refusal to test children for radiation. It is believed that identifying the process by which people emotionally responded to this information, and hence became gripped by an increased aversion to Fukushima, might be useful in risk communication when similar disasters and accidents occur in the future. There are few studies surveying how people feel about radiation in Fukushima and other regions in an unbiased form. Objective The purpose of this study is to identify how the feelings of local residents toward radiation changed according to Twitter. Methods We used approximately 19 million tweets in Japanese containing the words “radiation” (放射線), “radioactivity” (放射能), and “radioactive substances” (放射性物質) that were posted to Twitter over a 1-year period following the Fukushima nuclear accident. We used regional identifiers contained in tweets (ie, nouns, proper nouns, place names, postal codes, and telephone numbers) to categorize them according to their prefecture, and then analyzed the feelings toward those prefectures from the semantic orientation of the words contained in individual tweets (ie, positive impressions or negative impressions). Results Tweets about radiation increased soon after the earthquake and then decreased, and feelings about radiation trended positively. We determined that, on average, tweets associating Fukushima Prefecture with radiation show more positive feelings than those about other prefectures, but have trended negatively over time. We also found that as other tweets have trended positively, only bots and retweets about Fukushima Prefecture have trended negatively. Conclusions The number of tweets about radiation has decreased overall, and feelings about radiation have trended positively. However, the fact that tweets about Fukushima Prefecture trended negatively, despite decreasing in percentage, suggests that negative feelings toward Fukushima Prefecture have become more extreme. We found that while the bots and retweets that were not about Fukushima Prefecture gradually trended toward positive feelings, the bots and retweets about Fukushima Prefecture trended toward negative feelings.
- Subjects :
- Male
Fukushima Nuclear Accident
media_common.quotation_subject
Emotions
Health Informatics
radioactive hazard release
information dissemination
lcsh:Computer applications to medicine. Medical informatics
infodemiology
030218 nuclear medicine & medical imaging
Infodemiology
Twitter messaging
disaster medicine
03 medical and health sciences
infoveillance
0302 clinical medicine
Japan
infodemic
Surveys and Questionnaires
Humans
Social media
030212 general & internal medicine
media_common
Mass media
Original Paper
business.industry
lcsh:Public aspects of medicine
Sentiment analysis
lcsh:RA1-1270
Nuclear power
radiation
Attitude
Feeling
Infoveillance
radioactivity
lcsh:R858-859.7
Female
business
Psychology
belief in rumors
Social Media
Social psychology
Fukushima nuclear accident
Subjects
Details
- Language :
- English
- ISSN :
- 14388871
- Volume :
- 22
- Issue :
- 9
- Database :
- OpenAIRE
- Journal :
- Journal of Medical Internet Research
- Accession number :
- edsair.doi.dedup.....686b416df9a23dc93fdb9fc1ad38b658