<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1390-8634</journal-id>
<journal-title><![CDATA[Universitas-XXI, Revista de Ciencias Sociales y Humanas]]></journal-title>
<abbrev-journal-title><![CDATA[Universitas]]></abbrev-journal-title>
<issn>1390-8634</issn>
<publisher>
<publisher-name><![CDATA[Universidad Politécnica Salesiana]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1390-86342022000100149</article-id>
<article-id pub-id-type="doi">10.17163/uni.n36.2022.06</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Emociones, espacio público e imágenes urbanas en el contexto de COVID-19]]></article-title>
<article-title xml:lang="en"><![CDATA[Emotions, public space, and urban images in the context of COVID-19]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cabrera-Barona]]></surname>
<given-names><![CDATA[Pablo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Barragán-Ochoa]]></surname>
<given-names><![CDATA[Fernando]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Carrión]]></surname>
<given-names><![CDATA[Andrea]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Valdez]]></surname>
<given-names><![CDATA[Felipe]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[López-Sandoval]]></surname>
<given-names><![CDATA[María Fernanda]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,FLACSO  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Ecuador</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Instituto de Altos Estudios Nacionales  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Ecuador</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Instituto de Altos Estudios Nacionales  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Ecuador</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Pontificia Universidad Católica del Ecuador  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Ecuador</country>
</aff>
<aff id="Af5">
<institution><![CDATA[,FLACSO  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Ecuador</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>08</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>08</month>
<year>2022</year>
</pub-date>
<numero>36</numero>
<fpage>149</fpage>
<lpage>172</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_arttext&amp;pid=S1390-86342022000100149&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_abstract&amp;pid=S1390-86342022000100149&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_pdf&amp;pid=S1390-86342022000100149&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El confinamiento y las restricciones de movilidad durante la pandemia de COVID-19 han dado lugar a una serie de dilemas sobre el uso y percepción del espacio público, donde sus propiedades relacionales y contextuales pueden dar lugar a una diversidad de emociones. Con la aplicación de herramientas machine learning y social network analysis, exploramos emociones sobre el espacio público basadas en atributos de imágenes fotográficas en la ciudad de Quito, Ecuador, tomadas entre abril y junio de 2020. Los resultados muestran emociones positivas y negativas asociadas a un mismo atributo del paisaje urbano, mientras que atributos que pueden considerarse opuestos (como &#8220;brillante&#8221; y &#8220;sucio&#8221;) podrían tener mayor influencia en los sentimientos positivos sobre dicho espacio. Esta investigación abre un nuevo campo de estudio en la región sobre las emociones urbanas, y ofrece un mejor entendimiento de las percepciones de los ciudadanos sobre el espacio público durante la crisis de la pandemia.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract During the COVID-19 pandemic, confinement and mobility restrictions gave rise to different questions regarding the use and perceptions on public space, where the relational and contextual properties of this space may cause a diversity of emotions. We use machine learning and social network analysis to explore emotions in relation to the public space, based on attributes extracted from photos of the city of Quito, Ecuador, taken between April and June 2020. Our results show that an attribute of the urban landscape can be associated with positive and negative emotions, and that opposite attributes of the images (i.e., glossy and dirty) can both influence positive emotions regarding public space. This research inaugurates a new field of study in Latin America regarding urban emotions, and also supports a better understanding of citizen perceptions of the public space during the pandemic crisis.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Imágenes]]></kwd>
<kwd lng="es"><![CDATA[emociones]]></kwd>
<kwd lng="es"><![CDATA[COVID-19]]></kwd>
<kwd lng="es"><![CDATA[espacio público]]></kwd>
<kwd lng="es"><![CDATA[machine learning]]></kwd>
<kwd lng="es"><![CDATA[social network analysis]]></kwd>
<kwd lng="en"><![CDATA[Images]]></kwd>
<kwd lng="en"><![CDATA[emotions]]></kwd>
<kwd lng="en"><![CDATA[COVID-19]]></kwd>
<kwd lng="en"><![CDATA[public space]]></kwd>
<kwd lng="en"><![CDATA[machine learning]]></kwd>
<kwd lng="en"><![CDATA[social network analysis]]></kwd>
</kwd-group>
</article-meta>
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