Application of Data Mining Clustering for Patterns Analysis of Cyberbullying Surveys


Abstract:

In latest years, harassment or abuse through mobile devices and the Internet has been on the rise. This issue, better known as cyberbullying, is crueler and more dangerous than the traditional ways of bullying, largely due to the anonymity on social media or the Internet possibly generating consequences across the person’s lifetime. Therefore, different approaches have been developed in the search of alerting, informing, and preventing about cyberbullying situations such as the creation of regulations, issuing laws, or promoting technological approaches. This paper aims to find relevant patterns by applying clustering techniques, and to accomplish this goal, the survey titled the scale of victimization among adolescents through mobile phones and Internet (CYBVIC) has been used allowing to measure behaviors of harassment, aggression and social exclusion. The results obtained by the clustering can be used to combat this social problem due to this analysis highlights the seven most important questions and the hidden patterns among the filled responses.

Año de publicación:

2024

Keywords:

  • clustering algorithm
  • CYBERBULLYING
  • CYBVIC
  • data mining
  • Harassment

Fuente:

scopusscopus

Tipo de documento:

Other

Estado:

Acceso restringido

Áreas de conocimiento:

  • Minería de datos
  • Red social
  • Psicología social

Áreas temáticas de Dewey:

  • Métodos informáticos especiales
  • Interacción social
  • Criminología
Procesado con IAProcesado con IA

Objetivos de Desarrollo Sostenible:

  • ODS 10: Reducción de las desigualdades
  • ODS 16: Paz, justicia e instituciones sólidas
  • ODS 17: Alianzas para lograr los objetivos
Procesado con IAProcesado con IA