Conference paper Open Access

Discovery of complex anomalous patterns of sexual violence in El Salvador

De-Arteaga, Maria; Dubrawski, Artur


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  <identifier identifierType="DOI">10.5281/zenodo.571551</identifier>
  <creators>
    <creator>
      <creatorName>De-Arteaga, Maria</creatorName>
      <givenName>Maria</givenName>
      <familyName>De-Arteaga</familyName>
      <affiliation>Carnegie Mellon University</affiliation>
    </creator>
    <creator>
      <creatorName>Dubrawski, Artur</creatorName>
      <givenName>Artur</givenName>
      <familyName>Dubrawski</familyName>
      <affiliation>Carnegie Mellon University</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Discovery of complex anomalous patterns of sexual violence in El Salvador</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2017</publicationYear>
  <subjects>
    <subject>data mining</subject>
    <subject>anomaly detection</subject>
    <subject>data visulisation</subject>
    <subject>sexual violence</subject>
    <subject>El Salvador</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2017-05-04</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/571551</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.599175</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/dfp17</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;When sexual violence is a product of organized crime or social imaginary, the links between sexual violence episodes can be understood as a latent structure. With this assumption in place, we can use data science to uncover complex patterns. In this paper we focus on the use of data mining techniques to unveil complex anomalous spatio-temporal patterns of sexual violence. We illustrate their use by analyzing all reported rapes in El Salvador over a period of nine years. Through our analysis, we are able to provide evidence of phenomena that,to the best of our knowledge,have not been previously reported in literature. We devote special attention to a pattern we discover in the East, where underage victims report their boyfriends as perpetrators at anomalously high rates. Finally, we explain how such analyzes could be conducted in real-time, enabling early detection of emerging patterns to allow law enforcement agencies and policy makers to react accordingly. &lt;/p&gt;</description>
  </descriptions>
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