<?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>1405-5546</journal-id>
<journal-title><![CDATA[Computación y Sistemas]]></journal-title>
<abbrev-journal-title><![CDATA[Comp. y Sist.]]></abbrev-journal-title>
<issn>1405-5546</issn>
<publisher>
<publisher-name><![CDATA[Instituto Politécnico Nacional, Centro de Investigación en Computación]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-55462025000100283</article-id>
<article-id pub-id-type="doi">10.13053/cys-29-1-5506</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Enhancing the Detection of Sexist Messages through a Multi-Profile-Based Ensemble Approach]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Jiménez-Martínez]]></surname>
<given-names><![CDATA[Martha Paola]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[López-Nava]]></surname>
<given-names><![CDATA[Irvin Hussein]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Montes-y-Gómez]]></surname>
<given-names><![CDATA[Manuel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Centro de Investigación Científica y de Educación Superior de Ensenada  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Instituto Nacional de Astrofísica, Óptica y Electrónica  ]]></institution>
<addr-line><![CDATA[Puebla ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2025</year>
</pub-date>
<volume>29</volume>
<numero>1</numero>
<fpage>283</fpage>
<lpage>294</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-55462025000100283&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-55462025000100283&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-55462025000100283&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: Sexism in language perpetuates harmful stereotypes, especially in cultures with deeply ingrained traditional gender roles, such as Mexico. While detection of misogynistic content in English has advanced, detecting sexist language in Spanish is less explored. This study uses the EXIST corpus, annotated by various demographic groups, to examine differing perceptions of sexism across genders and ages. Our analysis finds significant perception discrepancies, with 25% of texts showing disagreements between male and female annotators. We propose an ensemble classification model that integrates outputs from gender-specific and age-specific models based on ROBERTuito, achieving an F1 score of 0.854. To gain insights into our best classifier&#8217;s decision-making, we present an error analysis based on the visualization of attention weights, which helps us identify the most relevant words in the detection of subtle sexism. Additionally, we leverage ChatGPT&#8217;s capabilities to model language nuances, generating potential interpretations of texts associated with the classifications provided by our approach. This study underscores the importance of demographic considerations in sexist language detection and demonstrates that combining diverse perspectives with advanced techniques can enhance detection in Spanish social media.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Sexism]]></kwd>
<kwd lng="en"><![CDATA[hierarchical attention networks]]></kwd>
<kwd lng="en"><![CDATA[transformers]]></kwd>
<kwd lng="en"><![CDATA[social media]]></kwd>
<kwd lng="en"><![CDATA[ensemble classification]]></kwd>
<kwd lng="en"><![CDATA[sexism detection]]></kwd>
</kwd-group>
</article-meta>
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<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Hovy]]></surname>
<given-names><![CDATA[E.]]></given-names>
</name>
</person-group>
<source><![CDATA[Hierarchical attention networks for document classification]]></source>
<year>2016</year>
<conf-name><![CDATA[ conference of the North American chapter of the association for computational linguistics: human language technologies]]></conf-name>
<conf-date>2016</conf-date>
<conf-loc> </conf-loc>
<page-range>1480-9</page-range></nlm-citation>
</ref>
</ref-list>
</back>
</article>
