High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea
<p dir="ltr">The Middle East respiratory syndrome coronavirus (MERS-CoV) was exported to Korea in 2015,<br>resulting in a threat to neighboring nations. We evaluated the possibility of using a digital surveillance<br>system based on web searches and social media data to m...
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| مؤلفون آخرون: | , , , , , |
| منشور في: |
2016
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إضافة وسم
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| _version_ | 1864513556416823296 |
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| author | Soo-Yong Shin (303252) |
| author2 | Dong-Woo Seo (493455) Jisun An (10230800) Haewoon Kwak (5747558) Sung-Han Kim (301612) Jin Gwack (418442) Min-Woo Jo (2610211) |
| author2_role | author author author author author author |
| author_facet | Soo-Yong Shin (303252) Dong-Woo Seo (493455) Jisun An (10230800) Haewoon Kwak (5747558) Sung-Han Kim (301612) Jin Gwack (418442) Min-Woo Jo (2610211) |
| author_role | author |
| dc.creator.none.fl_str_mv | Soo-Yong Shin (303252) Dong-Woo Seo (493455) Jisun An (10230800) Haewoon Kwak (5747558) Sung-Han Kim (301612) Jin Gwack (418442) Min-Woo Jo (2610211) |
| dc.date.none.fl_str_mv | 2016-09-06T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1038/srep32920 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/High_correlation_of_Middle_East_respiratory_syndrome_spread_with_Google_search_and_Twitter_trends_in_Korea/27101566 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Health sciences Epidemiology Health services and systems Public health Information and computing sciences Data management and data science Human-centred computing Digital surveillance system Web searches Social media data Outbreak monitoring Correlation analysis |
| dc.title.none.fl_str_mv | High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">The Middle East respiratory syndrome coronavirus (MERS-CoV) was exported to Korea in 2015,<br>resulting in a threat to neighboring nations. We evaluated the possibility of using a digital surveillance<br>system based on web searches and social media data to monitor this MERS outbreak. We collected the<br>number of daily laboratory-confirmed MERS cases and quarantined cases from May 11, 2015 to June 26,<br>2015 using the Korean government MERS portal. The daily trends observed via Google search and<br>Twitter during the same time period were also ascertained using Google Trends and Topsy. Correlations<br>among the data were then examined using Spearman correlation analysis. We found high correlations<br>(>0.7) between Google search and Twitter results and the number of confirmed MERS cases for the<br>previous three days using only four simple keywords: “MERS”, “메르스” (“MERS (in Korean)”),<br>“메르스” (“MERS symptoms (in Korean)”), and “메르스 병원” (“MERS hospital (in Korean)”).<br>Additionally, we found high correlations between the Google search and Twitter results and the number<br>of quarantined cases using the above keywords. This study demonstrates the possibility of using a<br>digital surveillance system to monitor the outbreak of MERS.</p><h2>Other Information</h2><p dir="ltr">Published in: Scientific Reports<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1038/srep32920" target="_blank">https://dx.doi.org/10.1038/srep32920</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_46f3c139f4b76a670a22c4dcae6d9f01 |
| identifier_str_mv | 10.1038/srep32920 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/27101566 |
| publishDate | 2016 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in KoreaSoo-Yong Shin (303252)Dong-Woo Seo (493455)Jisun An (10230800)Haewoon Kwak (5747558)Sung-Han Kim (301612)Jin Gwack (418442)Min-Woo Jo (2610211)Health sciencesEpidemiologyHealth services and systemsPublic healthInformation and computing sciencesData management and data scienceHuman-centred computingDigital surveillance systemWeb searchesSocial media dataOutbreak monitoringCorrelation analysis<p dir="ltr">The Middle East respiratory syndrome coronavirus (MERS-CoV) was exported to Korea in 2015,<br>resulting in a threat to neighboring nations. We evaluated the possibility of using a digital surveillance<br>system based on web searches and social media data to monitor this MERS outbreak. We collected the<br>number of daily laboratory-confirmed MERS cases and quarantined cases from May 11, 2015 to June 26,<br>2015 using the Korean government MERS portal. The daily trends observed via Google search and<br>Twitter during the same time period were also ascertained using Google Trends and Topsy. Correlations<br>among the data were then examined using Spearman correlation analysis. We found high correlations<br>(>0.7) between Google search and Twitter results and the number of confirmed MERS cases for the<br>previous three days using only four simple keywords: “MERS”, “메르스” (“MERS (in Korean)”),<br>“메르스” (“MERS symptoms (in Korean)”), and “메르스 병원” (“MERS hospital (in Korean)”).<br>Additionally, we found high correlations between the Google search and Twitter results and the number<br>of quarantined cases using the above keywords. This study demonstrates the possibility of using a<br>digital surveillance system to monitor the outbreak of MERS.</p><h2>Other Information</h2><p dir="ltr">Published in: Scientific Reports<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1038/srep32920" target="_blank">https://dx.doi.org/10.1038/srep32920</a></p>2016-09-06T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1038/srep32920https://figshare.com/articles/journal_contribution/High_correlation_of_Middle_East_respiratory_syndrome_spread_with_Google_search_and_Twitter_trends_in_Korea/27101566CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/271015662016-09-06T03:00:00Z |
| spellingShingle | High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea Soo-Yong Shin (303252) Health sciences Epidemiology Health services and systems Public health Information and computing sciences Data management and data science Human-centred computing Digital surveillance system Web searches Social media data Outbreak monitoring Correlation analysis |
| status_str | publishedVersion |
| title | High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea |
| title_full | High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea |
| title_fullStr | High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea |
| title_full_unstemmed | High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea |
| title_short | High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea |
| title_sort | High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea |
| topic | Health sciences Epidemiology Health services and systems Public health Information and computing sciences Data management and data science Human-centred computing Digital surveillance system Web searches Social media data Outbreak monitoring Correlation analysis |