Online Work Force Analyzes Social Media to Identify Consequences of an Unplanned School Closure – Using Technology to Prepare for the Next Pandemic
Identifieur interne : 000288 ( Pmc/Checkpoint ); précédent : 000287; suivant : 000289Online Work Force Analyzes Social Media to Identify Consequences of an Unplanned School Closure – Using Technology to Prepare for the Next Pandemic
Auteurs : Jeanette J. Rainey [États-Unis] ; Jasmine Kenney [États-Unis] ; Ben Wilburn [États-Unis] ; Ami Putman [États-Unis] ; Yenlik Zheteyeva [États-Unis] ; Megan O Ullivan [États-Unis]Source :
- PLoS ONE [ 1932-6203 ] ; 2016.
Abstract
During an influenza pandemic, the United States Centers for Disease Control and Prevention (CDC) may recommend school closures. These closures could have unintended consequences for students and their families. Publicly available social media could be analyzed to identify the consequences of an unplanned school closure.
As a proxy for an unplanned, pandemic-related school closure, we used the district-wide school closure due to the September 10–18, 2012 teachers’ strike in Chicago, Illinois. We captured social media posts about the school closure using the Radian6 social media-monitoring platform. An online workforce from Amazon Mechanical Turk categorized each post into one of two groups. The first group included relevant posts that described the impact of the closure on students and their families. The second group included irrelevant posts that described the political aspects of the strike or topics unrelated to the school closure. All relevant posts were further categorized as expressing a positive, negative, or neutral sentiment. We analyzed patterns of relevant posts and sentiment over time and compared our findings to household surveys conducted after other unplanned school closures.
We captured 4,546 social media posts about the district-wide school closure using our search criteria. Of these, 930 (20%) were categorized as relevant by the online workforce. Of the relevant posts, 619 (67%) expressed a negative sentiment, 51 (5%) expressed a positive sentiment, and 260 (28%) were neutral. The number of relevant posts, and especially those with a negative sentiment, peaked on day 1 of the strike. Negative sentiment expressed concerns about childcare, missed school lunches, and the lack of class time for students. This was consistent with findings from previously conducted household surveys.
Social media are publicly available and can readily provide information on the impact of an unplanned school closure on students and their families. Using social media to assess the impact of an unplanned school closure due to a public health event would be informative. An online workforce can effectively assist with the review process.
Url:
DOI: 10.1371/journal.pone.0163207
PubMed: 27655229
PubMed Central: 5031444
Affiliations:
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PMC:5031444Le document en format XML
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<front><div type="abstract" xml:lang="en"><sec id="sec001"><title>Background</title>
<p>During an influenza pandemic, the United States Centers for Disease Control and Prevention (CDC) may recommend school closures. These closures could have unintended consequences for students and their families. Publicly available social media could be analyzed to identify the consequences of an unplanned school closure.</p>
</sec>
<sec id="sec002"><title>Methods</title>
<p>As a proxy for an unplanned, pandemic-related school closure, we used the district-wide school closure due to the September 10–18, 2012 teachers’ strike in Chicago, Illinois. We captured social media posts about the school closure using the Radian6 social media-monitoring platform. An online workforce from Amazon Mechanical Turk categorized each post into one of two groups. The first group included relevant posts that described the impact of the closure on students and their families. The second group included irrelevant posts that described the political aspects of the strike or topics unrelated to the school closure. All relevant posts were further categorized as expressing a positive, negative, or neutral sentiment. We analyzed patterns of relevant posts and sentiment over time and compared our findings to household surveys conducted after other unplanned school closures.</p>
</sec>
<sec id="sec003"><title>Results</title>
<p>We captured 4,546 social media posts about the district-wide school closure using our search criteria. Of these, 930 (20%) were categorized as relevant by the online workforce. Of the relevant posts, 619 (67%) expressed a negative sentiment, 51 (5%) expressed a positive sentiment, and 260 (28%) were neutral. The number of relevant posts, and especially those with a negative sentiment, peaked on day 1 of the strike. Negative sentiment expressed concerns about childcare, missed school lunches, and the lack of class time for students. This was consistent with findings from previously conducted household surveys.</p>
</sec>
<sec id="sec004"><title>Conclusion</title>
<p>Social media are publicly available and can readily provide information on the impact of an unplanned school closure on students and their families. Using social media to assess the impact of an unplanned school closure due to a public health event would be informative. An online workforce can effectively assist with the review process.</p>
</sec>
</div>
</front>
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</author>
<author><name sortKey="Coster, Dc" uniqKey="Coster D">DC Coster</name>
</author>
</analytic>
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<biblStruct><analytic><author><name sortKey="Kiviniemi, Mt" uniqKey="Kiviniemi M">MT Kiviniemi</name>
</author>
<author><name sortKey="Ram, Pk" uniqKey="Ram P">PK Ram</name>
</author>
<author><name sortKey="Kozlowski, Lt" uniqKey="Kozlowski L">LT Kozlowski</name>
</author>
<author><name sortKey="Smith, Km" uniqKey="Smith K">KM Smith</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Agolory, Sg" uniqKey="Agolory S">SG Agolory</name>
</author>
<author><name sortKey="Barbot, O" uniqKey="Barbot O">O Barbot</name>
</author>
<author><name sortKey="Averhoff, F" uniqKey="Averhoff F">F Averhoff</name>
</author>
<author><name sortKey="Weiss, D" uniqKey="Weiss D">D Weiss</name>
</author>
<author><name sortKey="Wilson, E" uniqKey="Wilson E">E Wilson</name>
</author>
<author><name sortKey="Egger, J" uniqKey="Egger J">J Egger</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Dooyema, Ca" uniqKey="Dooyema C">CA Dooyema</name>
</author>
<author><name sortKey="Copeland, D" uniqKey="Copeland D">D Copeland</name>
</author>
<author><name sortKey="Sinclair, Jr" uniqKey="Sinclair J">JR Sinclair</name>
</author>
<author><name sortKey="Shi, J" uniqKey="Shi J">J Shi</name>
</author>
<author><name sortKey="Wilkins, M" uniqKey="Wilkins M">M Wilkins</name>
</author>
<author><name sortKey="Wells, E" uniqKey="Wells E">E Wells</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Tuarob, S" uniqKey="Tuarob S">S Tuarob</name>
</author>
<author><name sortKey="Tucker, Cs" uniqKey="Tucker C">CS Tucker</name>
</author>
<author><name sortKey="Salathe, M" uniqKey="Salathe M">M Salathé</name>
</author>
<author><name sortKey="Ram, N" uniqKey="Ram N">N Ram</name>
</author>
</analytic>
</biblStruct>
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</back>
</TEI>
<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS One</journal-id>
<journal-id journal-id-type="iso-abbrev">PLoS ONE</journal-id>
<journal-id journal-id-type="publisher-id">plos</journal-id>
<journal-id journal-id-type="pmc">plosone</journal-id>
<journal-title-group><journal-title>PLoS ONE</journal-title>
</journal-title-group>
<issn pub-type="epub">1932-6203</issn>
<publisher><publisher-name>Public Library of Science</publisher-name>
<publisher-loc>San Francisco, CA USA</publisher-loc>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">27655229</article-id>
<article-id pub-id-type="pmc">5031444</article-id>
<article-id pub-id-type="doi">10.1371/journal.pone.0163207</article-id>
<article-id pub-id-type="publisher-id">PONE-D-15-35449</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Social Sciences</subject>
<subj-group><subject>Sociology</subject>
<subj-group><subject>Communications</subject>
<subj-group><subject>Social Communication</subject>
<subj-group><subject>Social Media</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Computer and Information Sciences</subject>
<subj-group><subject>Network Analysis</subject>
<subj-group><subject>Social Networks</subject>
<subj-group><subject>Social Media</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Social Sciences</subject>
<subj-group><subject>Sociology</subject>
<subj-group><subject>Social Networks</subject>
<subj-group><subject>Social Media</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject>
<subj-group><subject>Epidemiology</subject>
<subj-group><subject>School Closures</subject>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Social Sciences</subject>
<subj-group><subject>Sociology</subject>
<subj-group><subject>Education</subject>
<subj-group><subject>Schools</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>People and Places</subject>
<subj-group><subject>Population Groupings</subject>
<subj-group><subject>Professions</subject>
<subj-group><subject>Teachers</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject>
<subj-group><subject>Infectious Diseases</subject>
<subj-group><subject>Viral Diseases</subject>
<subj-group><subject>Influenza</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject>
<subj-group><subject>Public and Occupational Health</subject>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject>
<subj-group><subject>Pediatrics</subject>
<subj-group><subject>Child Health</subject>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject>
<subj-group><subject>Public and Occupational Health</subject>
<subj-group><subject>Child Health</subject>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Social Sciences</subject>
<subj-group><subject>Sociology</subject>
<subj-group><subject>Communications</subject>
<subj-group><subject>Social Communication</subject>
<subj-group><subject>Social Media</subject>
<subj-group><subject>Twitter</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Computer and Information Sciences</subject>
<subj-group><subject>Network Analysis</subject>
<subj-group><subject>Social Networks</subject>
<subj-group><subject>Social Media</subject>
<subj-group><subject>Twitter</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Social Sciences</subject>
<subj-group><subject>Sociology</subject>
<subj-group><subject>Social Networks</subject>
<subj-group><subject>Social Media</subject>
<subj-group><subject>Twitter</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</article-categories>
<title-group><article-title>Online Work Force Analyzes Social Media to Identify Consequences of an Unplanned School Closure – Using Technology to Prepare for the Next Pandemic</article-title>
<alt-title alt-title-type="running-head">Online Work Force Analyzes Social Media about Unplanned School Closure</alt-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Rainey</surname>
<given-names>Jeanette J.</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
<xref ref-type="corresp" rid="cor001">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Kenney</surname>
<given-names>Jasmine</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Wilburn</surname>
<given-names>Ben</given-names>
</name>
<xref ref-type="aff" rid="aff002"><sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Putman</surname>
<given-names>Ami</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Zheteyeva</surname>
<given-names>Yenlik</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>O’Sullivan</surname>
<given-names>Megan</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff001"><label>1</label>
<addr-line>Division of Global Migration and Quarantine, Centers for Disease Control and Prevention, Atlanta, GA, United States of America</addr-line>
</aff>
<aff id="aff002"><label>2</label>
<addr-line>Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN, United States of America</addr-line>
</aff>
<contrib-group><contrib contrib-type="editor"><name><surname>Swerdlow</surname>
<given-names>David L.</given-names>
</name>
<role>Editor</role>
<xref ref-type="aff" rid="edit1"></xref>
</contrib>
</contrib-group>
<aff id="edit1"><addr-line>Pfizer Inc, UNITED STATES</addr-line>
</aff>
<author-notes><fn fn-type="COI-statement" id="coi001"><p><bold>Competing Interests: </bold>
The authors have declared that no competing interests exist.</p>
</fn>
<fn fn-type="con"><p><list list-type="simple"><list-item><p><bold>Conceptualization:</bold>
JR JK MO.</p>
</list-item>
<list-item><p><bold>Data curation:</bold>
JR JK BW MO.</p>
</list-item>
<list-item><p><bold>Formal analysis:</bold>
JR JK BW AP YZ MO.</p>
</list-item>
<list-item><p><bold>Funding acquisition:</bold>
JR.</p>
</list-item>
<list-item><p><bold>Investigation:</bold>
JR JK BW AP MO.</p>
</list-item>
<list-item><p><bold>Methodology:</bold>
JR JK AP BW YZ MO.</p>
</list-item>
<list-item><p><bold>Project administration:</bold>
JR MO.</p>
</list-item>
<list-item><p><bold>Resources:</bold>
JR YZ BW MO.</p>
</list-item>
<list-item><p><bold>Software:</bold>
JR JK BW AP YZ MO.</p>
</list-item>
<list-item><p><bold>Supervision:</bold>
JR BW.</p>
</list-item>
<list-item><p><bold>Validation:</bold>
JR JK BW AP YZ MO.</p>
</list-item>
<list-item><p><bold>Visualization:</bold>
JR JK MO.</p>
</list-item>
<list-item><p><bold>Writing – original draft:</bold>
JR JK MO.</p>
</list-item>
<list-item><p><bold>Writing – review & editing:</bold>
JR JK BW AP YZ MO.</p>
</list-item>
</list>
</p>
</fn>
<corresp id="cor001">* E-mail: <email>jkr7@cdc.gov</email>
</corresp>
</author-notes>
<pub-date pub-type="epub"><day>21</day>
<month>9</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="collection"><year>2016</year>
</pub-date>
<volume>11</volume>
<issue>9</issue>
<elocation-id>e0163207</elocation-id>
<history><date date-type="received"><day>19</day>
<month>8</month>
<year>2015</year>
</date>
<date date-type="accepted"><day>6</day>
<month>9</month>
<year>2016</year>
</date>
</history>
<permissions><license xlink:href="https://creativecommons.org/publicdomain/zero/1.0/"><license-p>This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/publicdomain/zero/1.0/">Creative Commons CC0</ext-link>
public domain dedication.</license-p>
</license>
</permissions>
<self-uri content-type="pdf" xlink:href="pone.0163207.pdf"></self-uri>
<abstract><sec id="sec001"><title>Background</title>
<p>During an influenza pandemic, the United States Centers for Disease Control and Prevention (CDC) may recommend school closures. These closures could have unintended consequences for students and their families. Publicly available social media could be analyzed to identify the consequences of an unplanned school closure.</p>
</sec>
<sec id="sec002"><title>Methods</title>
<p>As a proxy for an unplanned, pandemic-related school closure, we used the district-wide school closure due to the September 10–18, 2012 teachers’ strike in Chicago, Illinois. We captured social media posts about the school closure using the Radian6 social media-monitoring platform. An online workforce from Amazon Mechanical Turk categorized each post into one of two groups. The first group included relevant posts that described the impact of the closure on students and their families. The second group included irrelevant posts that described the political aspects of the strike or topics unrelated to the school closure. All relevant posts were further categorized as expressing a positive, negative, or neutral sentiment. We analyzed patterns of relevant posts and sentiment over time and compared our findings to household surveys conducted after other unplanned school closures.</p>
</sec>
<sec id="sec003"><title>Results</title>
<p>We captured 4,546 social media posts about the district-wide school closure using our search criteria. Of these, 930 (20%) were categorized as relevant by the online workforce. Of the relevant posts, 619 (67%) expressed a negative sentiment, 51 (5%) expressed a positive sentiment, and 260 (28%) were neutral. The number of relevant posts, and especially those with a negative sentiment, peaked on day 1 of the strike. Negative sentiment expressed concerns about childcare, missed school lunches, and the lack of class time for students. This was consistent with findings from previously conducted household surveys.</p>
</sec>
<sec id="sec004"><title>Conclusion</title>
<p>Social media are publicly available and can readily provide information on the impact of an unplanned school closure on students and their families. Using social media to assess the impact of an unplanned school closure due to a public health event would be informative. An online workforce can effectively assist with the review process.</p>
</sec>
</abstract>
<funding-group><funding-statement>The authors received no specific funding for this work.</funding-statement>
</funding-group>
<counts><fig-count count="2"></fig-count>
<table-count count="3"></table-count>
<page-count count="12"></page-count>
</counts>
<custom-meta-group><custom-meta id="data-availability"><meta-name>Data Availability</meta-name>
<meta-value>The social media posts analyzed for this project are available at <ext-link ext-link-type="uri" xlink:href="https://figshare.com">https://figshare.com</ext-link>
(DOI: <ext-link ext-link-type="uri" xlink:href="http://dx.doi.org/10.6084/m9.figshare.3463448">10.6084/m9.figshare.3463448</ext-link>
).</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
<notes><title>Data Availability</title>
<p>The social media posts analyzed for this project are available at <ext-link ext-link-type="uri" xlink:href="https://figshare.com">https://figshare.com</ext-link>
(DOI: <ext-link ext-link-type="uri" xlink:href="http://dx.doi.org/10.6084/m9.figshare.3463448">10.6084/m9.figshare.3463448</ext-link>
).</p>
</notes>
</front>
</pmc>
<affiliations><list><country><li>États-Unis</li>
</country>
<region><li>Géorgie (États-Unis)</li>
<li>Tennessee</li>
</region>
</list>
<tree><country name="États-Unis"><region name="Géorgie (États-Unis)"><name sortKey="Rainey, Jeanette J" sort="Rainey, Jeanette J" uniqKey="Rainey J" first="Jeanette J." last="Rainey">Jeanette J. Rainey</name>
</region>
<name sortKey="Kenney, Jasmine" sort="Kenney, Jasmine" uniqKey="Kenney J" first="Jasmine" last="Kenney">Jasmine Kenney</name>
<name sortKey="O Ullivan, Megan" sort="O Ullivan, Megan" uniqKey="O Ullivan M" first="Megan" last="O Ullivan">Megan O Ullivan</name>
<name sortKey="Putman, Ami" sort="Putman, Ami" uniqKey="Putman A" first="Ami" last="Putman">Ami Putman</name>
<name sortKey="Wilburn, Ben" sort="Wilburn, Ben" uniqKey="Wilburn B" first="Ben" last="Wilburn">Ben Wilburn</name>
<name sortKey="Zheteyeva, Yenlik" sort="Zheteyeva, Yenlik" uniqKey="Zheteyeva Y" first="Yenlik" last="Zheteyeva">Yenlik Zheteyeva</name>
</country>
</tree>
</affiliations>
</record>
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