Serveur d'exploration MERS

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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 : 000D24

Large-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 :

RBID : PMC:7129462

Descripteurs français

English descriptors

Abstract

Highlights

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:


Links toward previous steps (curation, corpus...)


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<p id="p0265">The emotional public responses to a nation-wide outbreak of Middle East respiratory syndrome (MERS) in Korea was analyzed.</p>
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<p id="p0270">Massive media outlet data was collected during the outbreak.</p>
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</back>
</TEI>
<affiliations>
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<country>
<li>Corée du Sud</li>
<li>États-Unis</li>
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<region>
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<country name="Corée du Sud">
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</tree>
</affiliations>
</record>

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