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<?covid-19-tdm?>
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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JMIR</journal-id>
      <journal-id journal-id-type="nlm-ta">J Med Internet Res</journal-id>
      <journal-title>Journal of Medical Internet Research</journal-title>
      <issn pub-type="epub">1438-8871</issn>
      <publisher>
        <publisher-name>JMIR Publications</publisher-name>
        <publisher-loc>Toronto, Canada</publisher-loc>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">v24i3e37841</article-id>
      <article-id pub-id-type="pmid">35275838</article-id>
      <article-id pub-id-type="doi">10.2196/37841</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Corrigenda and Addenda</subject>
        </subj-group>
        <subj-group subj-group-type="article-type">
          <subject>Corrigenda and Addenda</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Correction: COVID-19 Vaccine Tweets After Vaccine Rollout: Sentiment–Based Topic Modeling</article-title>
      </title-group>
      <contrib-group>
        <contrib id="contrib1" contrib-type="author">
          <name name-style="western">
            <surname>Huangfu</surname>
            <given-names>Luwen</given-names>
          </name>
          <degrees>PhD</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <xref rid="aff2" ref-type="aff">2</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0003-3926-7901</ext-link>
        </contrib>
        <contrib id="contrib2" contrib-type="author">
          <name name-style="western">
            <surname>Mo</surname>
            <given-names>Yiwen</given-names>
          </name>
          <degrees>MS</degrees>
          <xref rid="aff1" ref-type="aff">1</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0001-8671-8993</ext-link>
        </contrib>
        <contrib id="contrib3" contrib-type="author">
          <name name-style="western">
            <surname>Zhang</surname>
            <given-names>Peijie</given-names>
          </name>
          <degrees>MS</degrees>
          <xref rid="aff3" ref-type="aff">3</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0003-2468-4040</ext-link>
        </contrib>
        <contrib id="contrib4" contrib-type="author">
          <name name-style="western">
            <surname>Zeng</surname>
            <given-names>Daniel Dajun</given-names>
          </name>
          <degrees>PhD</degrees>
          <xref rid="aff3" ref-type="aff">3</xref>
          <xref rid="aff4" ref-type="aff">4</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-9046-222X</ext-link>
        </contrib>
        <contrib id="contrib5" contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>He</surname>
            <given-names>Saike</given-names>
          </name>
          <degrees>PhD</degrees>
          <xref rid="aff3" ref-type="aff">3</xref>
          <address>
            <institution>The State Key Laboratory of Management and Control for Complex Systems</institution>
            <institution>Institute of Automation</institution>
            <institution>Chinese Academy of Sciences</institution>
            <addr-line>95 Zhongguancun East Road, Haidian District</addr-line>
            <addr-line>Beijing, 100190</addr-line>
            <country>China</country>
            <phone>86 (010)82544537</phone>
            <email>saike.he@ia.ac.cn</email>
          </address>
          <xref rid="aff4" ref-type="aff">4</xref>
          <ext-link ext-link-type="orcid">https://orcid.org/0000-0002-2186-4524</ext-link>
        </contrib>
      </contrib-group>
      <aff id="aff1">
        <label>1</label>
        <institution>Fowler College of Business</institution>
        <institution>San Diego State University</institution>
        <addr-line>San Diego, CA</addr-line>
        <country>United States</country>
      </aff>
      <aff id="aff2">
        <label>2</label>
        <institution>Center for Human Dynamics in the Mobile Age</institution>
        <institution>San Diego State University</institution>
        <addr-line>San Diego, CA</addr-line>
        <country>United States</country>
      </aff>
      <aff id="aff3">
        <label>3</label>
        <institution>The State Key Laboratory of Management and Control for Complex Systems</institution>
        <institution>Institute of Automation</institution>
        <institution>Chinese Academy of Sciences</institution>
        <addr-line>Beijing</addr-line>
        <country>China</country>
      </aff>
      <aff id="aff4">
        <label>4</label>
        <institution>University of Chinese Academy of Sciences</institution>
        <addr-line>Beijing</addr-line>
        <country>China</country>
      </aff>
      <author-notes>
        <corresp>Corresponding Author: Saike He <email>saike.he@ia.ac.cn</email></corresp>
      </author-notes>
      <pub-date pub-type="collection">
        <month>3</month>
        <year>2022</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>11</day>
        <month>3</month>
        <year>2022</year>
      </pub-date>
      <volume>24</volume>
      <issue>3</issue>
      <elocation-id>e37841</elocation-id>
      <history>
        <date date-type="received">
          <day>8</day>
          <month>3</month>
          <year>2022</year>
        </date>
        <date date-type="accepted">
          <day>9</day>
          <month>3</month>
          <year>2022</year>
        </date>
      </history>
      <copyright-statement>©Luwen Huangfu, Yiwen Mo, Peijie Zhang, Daniel Dajun Zeng, Saike He. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 11.03.2022.</copyright-statement>
      <copyright-year>2022</copyright-year>
      <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/">
        <p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.</p>
      </license>
      <self-uri xlink:href="https://www.jmir.org/2022/3/e37841" xlink:type="simple"/>
      <related-article related-article-type="corrected-article" id="v24i2e31726" ext-link-type="doi" xlink:href="10.2196/31726" vol="24" page="e31726" xlink:type="simple">https://www.jmir.org/2022/2/e31726</related-article>
    </article-meta>
  </front>
  <body>
    <p>In “COVID-19 Vaccine Tweets After Vaccine Rollout: Sentiment–Based Topic Modeling” (J Med Internet Res 2022;24(2):e31726) the authors noted one error.</p>
    <p>In the originally published paper, <xref rid="figure8" ref-type="fig">Figure 8</xref>D showed incorrect colors. The top line was intended to be blue, and the bottom line was intended to be red.</p>
    <p>In the corrected version of the paper, <xref rid="figure8" ref-type="fig">Figure 8</xref>D has been revised as follows: the top line is now blue, and the bottom line is now red. The correct figure is provided below. The originally published <xref rid="figure8" ref-type="fig">Figure 8</xref> is in <xref ref-type="supplementary-material" rid="app1">Multimedia Appendix 1</xref>.</p>
    <p>The correction will appear in the online version of the paper on the JMIR Publications website on March 11, 2022, together with the publication of this correction notice. Because this was made after submission to PubMed, PubMed Central, and other full-text repositories, the corrected article has also been resubmitted to those repositories.</p>
    <fig id="figure8" position="float">
      <label>Figure 8</label>
      <caption>
        <p>Daily average positive and negative sentiment scores for (a) Johnson &#38; Johnson, (b) AstraZeneca, (c) Pfizer, and (d) Moderna vaccines and sentiment trends for (e) Johnson &#38; Johnson, (f) AstraZeneca, (g) Pfizer, and (h) Moderna vaccines.</p>
      </caption>
      <graphic xlink:href="jmir_v24i3e37841_fig8.png" alt-version="no" mimetype="image" position="float" xlink:type="simple"/>
    </fig>
  </body>
  <back>
    <app-group>
      <supplementary-material id="app1">
        <label>Multimedia Appendix 1</label>
        <p>The previously published Figure 8.</p>
        <media xlink:href="jmir_v24i3e37841_app1.png" xlink:title="PNG File , 502 KB"/>
      </supplementary-material>
    </app-group>
  </back>
</article>
