About: Twitter and Middle East respiratory syndrome, South Korea, 2015: A multi-lingual study

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About: Twitter and Middle East respiratory syndrome, South Korea, 2015: A multi-lingual study Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Twitter and Middle East respiratory syndrome, South Korea, 2015: A multi-lingual study
Creator	Fu, King-Wa Liang, Hai Chan, Chung-Hong Liu, Zhaochong Yin, Jingjing Zeng, Jing Fung, Chun-Hai Tse, Ho Tsz, Zion
Source	Elsevier; Medline; PMC
abstract	BACKGROUND: Different linguo-cultural communities might react to an outbreak differently. The 2015 South Korean MERS outbreak presented an opportunity for us to compare tweets responding to the same outbreak in different languages. METHODS: We obtained a 1% sample through Twitter streaming application programming interface from June 1 to 30, 2015. We identified MERS-related tweets with keywords such as ‘MERS’ and its translation in five different languages. We translated non-English tweets into English for statistical comparison. RESULTS: We retrieved MERS-related Twitter data in five languages: Korean (N = 21,823), English (N = 4024), Thai (N = 2084), Japanese (N = 1334) and Indonesian (N = 1256). Categories of randomly selected user profiles (p < 0.001) and the top 30 sources of retweets (p < 0.001) differed between the five language corpora. Among the randomly selected user profiles, K-pop fans ranged from 4% in the Korean corpus to 70% in the Thai corpus; media ranged from 0% (Thai) to 14% (Indonesian); political advocates ranged from 0% (Thai) to 19% (Japanese); medical professionals ranged from 0% (Thai) to 7% (English). Among the top 30 sources of retweets for each corpus (150 in total), 70 (46.7%) were media; 29 (19.3%) were K-pop fans; 7 (4.7%) were political; 9 (6%) were medical; and 35 (23.3%) were categorized as ‘Others’. We performed chi-square feature selection and identified the top 20 keywords that were most unique to each corpus. CONCLUSION: Different linguo-cultural communities exist on Twitter and they might react to the same outbreak differently. Understanding audiences' unique Twitter cultures will allow public health agencies to develop appropriate Twitter health communication strategies.
has issue date	2017-09-18(xsd:dateTime)
bibo:doi	10.1016/j.idh.2017.08.005
bibo:pmid	30479298
has license	no-cc
sha1sum (hex)	e588aff0a56cff664fe91d965b9a771e71d4e595
schema:url	https://doi.org/10.1016/j.idh.2017.08.005
resource representing a document's title	Twitter and Middle East respiratory syndrome, South Korea, 2015: A multi-lingual study
has PubMed Central identifier	PMC7185480
has PubMed identifier	30479298
schema:publication	Infect Dis Health
resource representing a document's body	covid:e588aff0a56cff664fe91d965b9a771e71d4e595#body_text
is schema:about of	named entity 'languages' named entity 'translated' named entity 'K-pop fans' named entity 'All rights reserved' named entity 'compare' named entity 'tweets' named entity 'Results' named entity 'randomly' named entity 'Thai' named entity '2015' named entity 'STUDY' named entity 'CHI-SQUARE' named entity 'INFECTION PREVENTION' named entity 'ALLOW' named entity 'MEDIA' named entity 'AUDIENCES' named entity '2015' named entity 'COLLEGE' named entity 'SELECTED' named entity 'RELATED' named entity 'ADVOCATES' named entity 'TWITTER' named entity 'CATEGORIES' named entity 'IDENTIFIED' named entity 'SOUTH' named entity 'ITS' named entity 'PROFESSIONALS' named entity 'HEALTH COMMUNICATION' named entity '30%' named entity '4024' named entity '28150' named entity 'DIFFERENT' named entity 'TRANSLATED' named entity '70%' named entity '0.001' named entity 'SOUTH KOREA' named entity 'MULTI' named entity 'TWITTER' named entity 'RESULTS' named entity 'REACT' named entity 'APPROPRIATE' named entity 'SOURCES' named entity 'BACKGROUND' named entity 'KEYWORDS' named entity 'PERFORMED' named entity '28P' named entity 'PRESENTED' named entity 'MERS' named entity 'OBTAINED' named entity 'STATISTICAL' named entity 'TOTAL' named entity 'FANS' named entity 'JUNE' named entity 'COMMUNITIES' named entity 'UNIQUE' named entity 'LANGUAGES' named entity 'PUBLIC HEALTH' named entity 'CULTURES' named entity 'UNDERSTANDING' named entity 'MIDDLE EAST RESPIRATORY SYNDROME' named entity '2015' named entity 'LINGUAL' named entity 'THAI' named entity 'SAMPLE' named entity 'USER' named entity 'JAPANESE' named entity 'LANGUAGE' named entity '1256' named entity 'PREVENTION AND CONTROL' named entity 'DATA' named entity 'FEATURE SELECTION' named entity 'TRANSLATION' named entity 'RIGHTS'

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