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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

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          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.

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          Most cited references28

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          Twitter under crisis

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            You Are What You Tweet: Connecting the Geographic Variation in America’s Obesity Rate to Twitter Content

            We conduct a detailed investigation of the relationship among the obesity rate of urban areas and expressions of happiness, diet and physical activity on social media. We do so by analyzing a massive, geo-tagged data set comprising over 200 million words generated over the course of 2012 and 2013 on the social network service Twitter. Among many results, we show that areas with lower obesity rates: (1) have happier tweets and frequently discuss (2) food, particularly fruits and vegetables, and (3) physical activities of any intensity. Additionally, we provide evidence that each of these results offer different and unique insight into the variation of the obesity rate in urban areas within the United States. Our work shows how the contents of social media may potentially be used to estimate real-time, population-scale measures of factors related to obesity.
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              Temporal and spatiotemporal investigation of tourist attraction visit sentiment on Twitter

              In this paper, we propose a sentiment-based approach to investigate the temporal and spatiotemporal effects on tourists’ emotions when visiting a city’s tourist destinations. Our approach consists of four steps: data collection and preprocessing from social media; visitor origin identification; visit sentiment identification; and temporal and spatiotemporal analysis. The temporal and spatiotemporal dimensions include day of the year, season of the year, day of the week, location sentiment progression, enjoyment measure, and multi-location sentiment progression. We apply this approach to the city of Chicago using over eight million tweets. Results show that seasonal weather, as well as special days and activities like concerts, impact tourists’ emotions. In addition, our analysis suggests that tourists experience greater levels of enjoyment in places such as observatories rather than zoos. Finally, we find that local and international visitors tend to convey negative sentiment when visiting more than one attraction in a day whereas the opposite holds for out of state visitors.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J. Med. Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                September 2020
                2 September 2020
                : 22
                : 9
                : e18662
                Affiliations
                [1 ] Graduate School of Health Sciences Hokkaido University Sapporo Japan
                [2 ] Quantum Medical Science Directorate National Institutes for Quantum and Radiological Science and Technology Chiba Japan
                [3 ] Hokkaido University of Education Iwamizawa Japan
                [4 ] Faculty of Health Sciences Hokkaido University Sapporo Japan
                [5 ] Department of Radiological Technology Hokkaido University of Science Sapporo Japan
                Author notes
                Corresponding Author: Katsuhiko Ogasawara oga@ 123456hs.hokudai.ac.jp
                Author information
                https://orcid.org/0000-0002-6340-3646
                https://orcid.org/0000-0002-1030-2788
                https://orcid.org/0000-0003-3364-7719
                https://orcid.org/0000-0002-8626-014X
                https://orcid.org/0000-0003-4236-8228
                https://orcid.org/0000-0002-2365-749X
                https://orcid.org/0000-0001-5474-7861
                Article
                v22i9e18662
                10.2196/18662
                7495261
                32876574
                db903edc-ef5b-4411-a7dd-c6130311ae3b
                ©Shin Hasegawa, Teppei Suzuki, Ayako Yagahara, Reiko Kanda, Tatsuo Aono, Kazuaki Yajima, Katsuhiko Ogasawara. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 02.09.2020.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 11 March 2020
                : 13 April 2020
                : 8 June 2020
                : 11 June 2020
                Categories
                Original Paper
                Original Paper

                Medicine
                fukushima nuclear accident,twitter messaging,radiation,radioactivity,radioactive hazard release,information dissemination,belief in rumors,disaster medicine,infodemiology,infoveillance,infodemic

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