Vol. 7 (2023): RECIE. Revista Electrónica Científica de Investigación Educativa (enero-diciembre)
F) Tecnologías de la información y la comunicación en educación

Machine Learning for the detection of risk situations through the use of dating apps among university students

Mariana Carolyn Cruz Mendoza
Tecnológico Nacional de México/Instituto Tecnológico Superior de Misantla, Veracruz, México
Bio
Roberto Ángel Meléndez Armenta
Tecnológico Nacional de México/Instituto Tecnológico Superior de Misantla, Veracruz, México
Bio
Narendra Velázquez Carmona
Tecnológico Nacional de México/Tecnológico de Estudios Superiores de Valle de Bravo, Estado de México
Bio
Portada-7

Published 2023-12-31

Keywords

  • Data analysis,
  • students,
  • social media,
  • violence,
  • social safety
  • Análisis de datos,
  • estudiantes,
  • redes sociales,
  • violencia,
  • seguridad social

How to Cite

Cruz Mendoza, M. C., Meléndez Armenta, R. Ángel, & Velázquez Carmona, N. (2023). Machine Learning for the detection of risk situations through the use of dating apps among university students. RECIE. Revista Electrónica Científica De Investigación Educativa, 7, e2012. https://doi.org/10.33010/recie.v7i0.2012

Abstract

In the current era of social media, human communication and interactions have largely shifted to the virtual realm. However, this transition has also given rise to the emergence of violent behaviors, which saw a significant increase during the global COVID-19 pandemic. This research project arises to address the growing concerns regarding safety and the prevention of risky situations on dating applications. In this endeavor, students from various academic programs at the Tecnológico de Estudios Superiores de Valle de Bravo (TESVB) actively participate, providing a comprehensive view of the use of dating apps in a university setting. The analysis of the collected information will enable the identification of behavioral patterns and signs of violent tendencies among Tinder users. It is essential to comprehend the current dynamics of online interactions and contribute to the development of measures that encompass not only romantic relationships but also friendships and other types of relationships, by implementing data collection instruments and data analysis tools to visualize the experiences and perceptions of dating app users, especially young university students, who may have different perspectives on the risky situations they encounter in their virtual, family, and academic environment.

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