<?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>0012-7353</journal-id>
<journal-title><![CDATA[DYNA]]></journal-title>
<abbrev-journal-title><![CDATA[Dyna rev.fac.nac.minas]]></abbrev-journal-title>
<issn>0012-7353</issn>
<publisher>
<publisher-name><![CDATA[Universidad Nacional de Colombia]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0012-73532023000100064</article-id>
<article-id pub-id-type="doi">10.15446/dyna.v90n225.104189</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Do Internet search patterns predict election results? An analysis of the 2022 presidential election in Colombia using a reproducible descriptive analytics framework]]></article-title>
<article-title xml:lang="es"><![CDATA[¿Los patrones de búsqueda en Internet predicen los resultados de las elecciones? Un análisis de las elecciones presidenciales de 2022 en Colombia utilizando un marco de análisis descriptivo reproducible]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pérez-Rave]]></surname>
<given-names><![CDATA[Jorge Iván]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Maya-Restrepo]]></surname>
<given-names><![CDATA[María Alejandra]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[González-Echavarría]]></surname>
<given-names><![CDATA[Favián]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,IDINNOV Research Group  ]]></institution>
<addr-line><![CDATA[Medellín ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad de Antioquia Departamento de Ingeniería Industrial ]]></institution>
<addr-line><![CDATA[Medellín ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2023</year>
</pub-date>
<volume>90</volume>
<numero>225</numero>
<fpage>64</fpage>
<lpage>70</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0012-73532023000100064&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0012-73532023000100064&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0012-73532023000100064&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Recent works have highlighted the relevance of Google Trends data for predicting electoral processes. However, the potential for the generalization of this evidence is still limited and there is still no consensus on the most appropriate method for performing analytics with data from this tool for this purpose. This study examines whether such data are useful for predicting presidential election results, taking as a case study the recent Colombian presidential election for 2022-2026, using a proposed reproducible framework of descriptive analytics in R. A sample of 1,020 observations was considered. All the analysis scenarios (considering Google, YouTube and both) were correct regarding the candidate who was finally elected by the citizens, and the best estimate was obtained by using data from one day before the election (less than 2% distance from the true result). This work is a cost-effective alternative for predicting presidential election results.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen Trabajos recientes resaltan la pertinencia de los datos de Tendencias de Google para predecir procesos electorales. Sin embargo, dicha evidencia aún no es generalizable y no hay consenso sobre la forma más adecuada de hacer analítica con datos de esta herramienta para este &#64257;n. El estudio examina si tales datos son útiles para predecir resultados de elecciones presidenciales, tomando como caso de estudio la elección de presidente de Colombia 2022-2026 (segunda vuelta), usando un marco reproducible propuesto de analítica descriptiva en R. Se tuvo una muestra de 1020 observaciones. Todos los escenarios de análisis (considerando Google, YouTube y ambos) acertaron respecto al candidato que fue elegido por los ciudadanos, siendo la mejor estimación aquella arrojada por los datos de un día antes de las elecciones: inferior de 2% de distancia respecto al verdadero porcentaje de votación de cada candidato. Esta propuesta es una alternativa costo-efectiva para predecir resultados de elecciones presidenciales.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[electoral analytics]]></kwd>
<kwd lng="en"><![CDATA[Google Trends]]></kwd>
<kwd lng="en"><![CDATA[analytics]]></kwd>
<kwd lng="en"><![CDATA[descriptive analytics]]></kwd>
<kwd lng="en"><![CDATA[presidential elections]]></kwd>
<kwd lng="es"><![CDATA[analítica electoral]]></kwd>
<kwd lng="es"><![CDATA[tendencias de Google]]></kwd>
<kwd lng="es"><![CDATA[analítica descriptiva]]></kwd>
<kwd lng="es"><![CDATA[elecciones presidenciales]]></kwd>
</kwd-group>
</article-meta>
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<surname><![CDATA[Makram]]></surname>
<given-names><![CDATA[O.M.]]></given-names>
</name>
<name>
<surname><![CDATA[Elhady]]></surname>
<given-names><![CDATA[M.]]></given-names>
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<name>
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<given-names><![CDATA[N.T]]></given-names>
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</person-group>
<article-title xml:lang=""><![CDATA[Prediction of Zika-confirmed cases in Brazil and Colombia using Google Trends]]></article-title>
<source><![CDATA[Epidemiology and Infection]]></source>
<year>2018</year>
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</back>
</article>
