Social Big Data Analysis of Information Spread and Perceived Infection Risk During the 2015 Middle East Respiratory Syndrome Outbreak in South Korea.
Identifieur interne : 000B88 ( Main/Exploration ); précédent : 000B87; suivant : 000B89Social Big Data Analysis of Information Spread and Perceived Infection Risk During the 2015 Middle East Respiratory Syndrome Outbreak in South Korea.
Auteurs : Juyoung Song [États-Unis] ; Tae Min Song [Corée du Sud] ; Dong-Chul Seo [États-Unis] ; Dal-Lae Jin [Corée du Sud] ; Jung Sun Kim [Corée du Sud]Source :
- Cyberpsychology, behavior and social networking [ 2152-2723 ] ; 2017.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- epidemiology : Coronavirus Infections, Republic of Korea.
- methods : Information Dissemination.
- statistics & numerical data : Disease Outbreaks.
- Humans, Middle East Respiratory Syndrome Coronavirus, Social Media.
Abstract
We investigated online diffusion of information, spread of fear, and perceived risk of infection to Middle East Respiratory Syndrome (MERS) as cases of MERS spread rapidly and dozens of fatalities occurred in South Korea in May-June of 2015. This study retrieved 8,671,695 MERS-related online documents from May 20 to June 18, 2015, from 171 Korean online channels and analyzed such documents by using multilevel models and data mining with Apriori algorithm association analysis. We used R software (version 3.2.1) for the association analysis data mining and visualization. Buzz with negative emotions (i.e., anxiety or fear) was more prevalent in online discussion boards, Twitter, and online cafes than news sites and blogs. News buzz (b = 0.21, p < 0.001), but not rumor buzz (b = 0.06, p = 0.308), was associated with positive MERS emotions (i.e., being calm or composed). The mention of eating immunity-boosting food in the news led to a 94 percent chance of a positive MERS emotion and that such a chance of showing a positive emotion was 4.75 times higher than that without such a mention (support of 0.001, confidence of 0.94, and lift of 4.75). Even with the same precautionary messages that were disseminated, they yielded the opposite emotional reactions to people depending on the channel through which the messages were communicated. In the face of a novel and highly contagious disease such as MERS, the government must deploy a response system that includes provision and dissemination of reliable information and inhibits online diffusion of false information.
DOI: 10.1089/cyber.2016.0126
PubMed: 28051336
Affiliations:
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xml:lang="en">We investigated online diffusion of information, spread of fear, and perceived risk of infection to Middle East Respiratory Syndrome (MERS) as cases of MERS spread rapidly and dozens of fatalities occurred in South Korea in May-June of 2015. This study retrieved 8,671,695 MERS-related online documents from May 20 to June 18, 2015, from 171 Korean online channels and analyzed such documents by using multilevel models and data mining with Apriori algorithm association analysis. We used R software (version 3.2.1) for the association analysis data mining and visualization. Buzz with negative emotions (i.e., anxiety or fear) was more prevalent in online discussion boards, Twitter, and online cafes than news sites and blogs. News buzz (b = 0.21, p < 0.001), but not rumor buzz (b = 0.06, p = 0.308), was associated with positive MERS emotions (i.e., being calm or composed). The mention of eating immunity-boosting food in the news led to a 94 percent chance of a positive MERS emotion and that such a chance of showing a positive emotion was 4.75 times higher than that without such a mention (support of 0.001, confidence of 0.94, and lift of 4.75). Even with the same precautionary messages that were disseminated, they yielded the opposite emotional reactions to people depending on the channel through which the messages were communicated. In the face of a novel and highly contagious disease such as MERS, the government must deploy a response system that includes provision and dissemination of reliable information and inhibits online diffusion of false information.</div></front></TEI><affiliations><list><country><li>Corée du Sud</li><li>États-Unis</li></country><region><li>Indiana</li><li>Pennsylvanie</li><li>Région capitale de Séoul</li></region><settlement><li>Séoul</li></settlement></list><tree><country name="États-Unis"><region name="Pennsylvanie"><name sortKey="Song, Juyoung" sort="Song, Juyoung" uniqKey="Song J" first="Juyoung" last="Song">Juyoung Song</name></region><name sortKey="Seo, Dong Chul" sort="Seo, Dong Chul" uniqKey="Seo D" first="Dong-Chul" last="Seo">Dong-Chul Seo</name></country><country name="Corée du Sud"><region name="Région capitale de Séoul"><name sortKey="Song, Tae Min" sort="Song, Tae Min" uniqKey="Song T" first="Tae Min" last="Song">Tae Min Song</name></region><name sortKey="Jin, Dal Lae" sort="Jin, Dal Lae" uniqKey="Jin D" first="Dal-Lae" last="Jin">Dal-Lae Jin</name><name sortKey="Kim, Jung Sun" sort="Kim, Jung Sun" uniqKey="Kim J" first="Jung Sun" last="Kim">Jung Sun Kim</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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