Large-scale machine learning of media outlets for understanding public reactions to nation-wide viral infection outbreaks
Identifieur interne : 000D23 ( Main/Exploration ); précédent : 000D22; suivant : 000D24Large-scale machine learning of media outlets for understanding public reactions to nation-wide viral infection outbreaks
Auteurs : Sungwoon Choi [Corée du Sud] ; Jangho Lee [Corée du Sud] ; Min-Gyu Kang [Corée du Sud] ; Hyeyoung Min [Corée du Sud] ; Yoon-Seok Chang [Corée du Sud] ; Sungroh Yoon [Corée du Sud, États-Unis]Source :
- Methods (San Diego, Calif.) [ 1046-2023 ] ; 2017.
Descripteurs français
- KwdFr :
- MESH :
- pathogénicité : Coronavirus du syndrome respiratoire du Moyen-Orient.
- virologie : Infections à coronavirus.
- épidémiologie : Infections à coronavirus.
- Apprentissage machine, Flambées de maladies, Humains, Mass-médias, République de Corée.
English descriptors
- KwdEn :
- MESH :
- epidemiology : Coronavirus Infections.
- pathogenicity : Middle East Respiratory Syndrome Coronavirus.
- virology : Coronavirus Infections.
- Disease Outbreaks, Humans, Machine Learning, Mass Media, Republic of Korea.
Abstract
The emotional public responses to a nation-wide outbreak of Middle East respiratory syndrome (MERS) in Korea was analyzed. Massive media outlet data was collected during the outbreak. An intriguing loop of information transfers between the media and the public was discovered. This method would be helpful for alleviating the unnecessary fear and overreaction of the public regarding infectious diseases.
Url:
DOI: 10.1016/j.ymeth.2017.07.027
PubMed: 28813689
PubMed Central: 7129462
Affiliations:
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Le document en format XML
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<term>Coronavirus Infections (virology)</term>
<term>Disease Outbreaks</term>
<term>Humans</term>
<term>Machine Learning</term>
<term>Mass Media</term>
<term>Middle East Respiratory Syndrome Coronavirus (pathogenicity)</term>
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<term>Humains</term>
<term>Infections à coronavirus (virologie)</term>
<term>Infections à coronavirus (épidémiologie)</term>
<term>Mass-médias</term>
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<keywords scheme="MESH" qualifier="pathogenicity" xml:lang="en"><term>Middle East Respiratory Syndrome Coronavirus</term>
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<front><div type="abstract" xml:lang="en"><title>Highlights</title>
<p><list list-type="simple" id="l0005"><list-item id="u0005"><label>•</label>
<p id="p0265">The emotional public responses to a nation-wide outbreak of Middle East respiratory syndrome (MERS) in Korea was analyzed.</p>
</list-item>
<list-item id="u0010"><label>•</label>
<p id="p0270">Massive media outlet data was collected during the outbreak.</p>
</list-item>
<list-item id="u0015"><label>•</label>
<p id="p0275">An intriguing loop of information transfers between the media and the public was discovered.</p>
</list-item>
<list-item id="u0020"><label>•</label>
<p id="p0280">This method would be helpful for alleviating the unnecessary fear and overreaction of the public regarding infectious diseases.</p>
</list-item>
</list>
</p>
</div>
</front>
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</TEI>
<affiliations><list><country><li>Corée du Sud</li>
<li>États-Unis</li>
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<region><li>Californie</li>
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</tree>
</affiliations>
</record>
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