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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ICA-Proc</journal-id>
<journal-title-group>
<journal-title>Proceedings of the ICA</journal-title>
<abbrev-journal-title abbrev-type="publisher">ICA-Proc</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Proc. Int. Cartogr. Assoc.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2570-2092</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/ica-proc-2-157-2019</article-id>
<title-group>
<article-title>Research on event perception based on geo-tagged social media data</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zhu</surname>
<given-names>Ruoxin</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zuo</surname>
<given-names>Chenyu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Lin</surname>
<given-names>Diao</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Chair of Cartography, Technical University of Munich, 80333 Munich, Germany</addr-line>
</aff>
<pub-date pub-type="epub">
<day>10</day>
<month>07</month>
<year>2019</year>
</pub-date>
<volume>2</volume>
<elocation-id>157</elocation-id>
<permissions>
<copyright-statement>Copyright: © 2019 Ruoxin Zhu et al.</copyright-statement>
<copyright-year>2019</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
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<self-uri xlink:href="https://ica-proc.copernicus.org/articles/ica-proc-2-157-2019.pdf">The full text article is available as a PDF file from https://ica-proc.copernicus.org/articles/ica-proc-2-157-2019.pdf</self-uri>
<abstract>
<p>Technological advancement makes information dissemination more convenient. When a notable event occurs, social media serves a popular platform for citizens to share event-related information. Therefore, in the information age, how to effectively observe the event and improve event management ability is an open question worthy of attention. Traditional social survey methods and various automatic sensors have been widely used to monitor the specific event. However, widely used social media service provides a unique approach for the event study with individuals as smart sensors. How to perceive an event through social media data has triggered a series of researches. Currently, we can find when, where what happened and induced impact based on geo-tagged social media data. However, event study based on social media is still in its infancy. This paper provides an overview of event study based on geo-tagged social media data. Firstly, we introduce the event model and the characteristics of social media data. Then, how to detect and trace event, how to analyze event impact and visually express obtained knowledge are discussed respectively. Subsequently, based on the existing researches, we propose further questions and conclude.</p>
</abstract>
<counts><page-count count="8"/></counts>
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