Evaluation of addiction levels to social networks in university students using a Markov chain

The addiction to social networks by young people is something that has been increasing in recent years. It has led to the application of methods to analyze the behavior of this variable and generate strategies that help mitigate its negative impacts. This research contributes to this, using a Markovian model and a regression model in a novel way. In the first instance, the variable time of permanence in social networks is analyzed by considering socio-affective, socio-economic, academic and demographic factors. Then, the Markovian model is built. Finally, the incidence of associated factors in addiction to social networks is analyzed. The results indicate that the probability of using social networks in less than one hour is 33%, and between two and three hours is 62%. Most students then spend many hours on social networks, affecting academic aspects, job performance, interpersonal relationships, and others.

• Autores: Obredor Baldovino, Thalía; Salas-Navarro, Katherinne; Moreno-Cruz, Jeffrey; Fajardo-Pérez, Carlos
• Tipo de recurso: Article of investigation
• Fecha de publicación: 2022
• Institución: Corporación Universidad de la Costa
• Repositorio: REDICUC - Repositorio CUC
• Idioma: eng
• OAI Identifier: oai:repositorio.cuc.edu.co:11323/10823
• Acceso en línea: https://hdl.handle.net/11323/10823; https://repositorio.cuc.edu.co/
• Palabra clave: Markov chain; Social networks; Regression model; Addiction
• Rights: openAccess
• License: Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)