CORDERO GARCÍA, G., RAMÍREZ DUEÑAS, J.M. y SÁNCHEZ FERNÁNDEZ, S., 2025. La brecha ideológica de género en la Generación Z en España. Revista española de ciencia política, no. 67, pp. 69-99. ISSN 1575-6548.
In recent years, an ideological gap between young men and young women in Spain has been observed. With the aim of understanding this phenomenon, we delve deeply into its origins, studying the evolution that has occurred since the 1980s in two components that traditionally explain ideological self-placement: attitudes and voting behavior. The results show that the differences between men and women are more pronounced in Generation Z (aged 18 to 25) than in other age groups, primarily due to a shift in trend among men. Young individuals in Generation Z tend to align with and support parties closer to the right, displaying increasingly conservative attitudes and less favorability towards equality compared to women in the same generation. Moreover, they exhibit the lowest levels of support for democracy, reaching unprecedented levels since the 1970s. Investigating the origins of this new ideological gap is essential as a first step to comprehend its potential political ramifications.
NICOLÁS-SANS, R. y NAVARRO MARTÍNEZ, R., 2025. Percepción y detección del ciberacoso: comparativa entre la comunidad educativa y las GenAI. Comunicar: Revista Científica de Comunicación y Educación, no. 80, pp. 1-12. ISSN 1134-3478.
Bullying involves repeated and aggressive behaviors to intimidate or harm others, with cyberbullying being the kind that benefits from digital platforms to direct such messages. They both have serious consequences on students’ mental health and academic performance, demanding prevention and intervention strategies, including teacher training and the use of tools to detect these behaviors in university environments. Artificial Intelligence (AI), specifically generative AI, can automatically detect offensive language on digital platforms, resulting in an effective tool combating cyberbullying. This study investigates the capacity of members within a university community—students, faculty, and administrative staff—to perceive and detect cyberbullying in social media messages. The research utilizes generative AI tools to assess their effectiveness in recognizing cyberbullying patterns, comparing their results against expert evaluations. Results indicate that faculty members are most effective in identifying cyberbullying, while students show greater leniency, highlighting the need for targeted educational interventions. The generative AI models, despite limitations, demonstrate potential for early cyberbullying detection. Findings underscore the importance of training within educational communities and suggest that AI tools, when integrated into preventive programs, can enhance early intervention and promote safer digital environments.
PADILLA LÓPEZ, L., 2025. El proxenetismo digital y la captación de menores en redes sociales: un análisis sobre la hipersexualización y el empoderamiento en plataformas online. Revista de Victimología, no. 19, pp. 213-250. ISSN 2385-779X.
This study examines the phenomenon of digital exploitation and the recruitment of minors on online platforms. It analyzes how predators use social media to sexually exploit young people and adolescents, presenting this behavior under the guise of ‘empowerment’. Through the applicationof a mixed-methods approach, the study explores the recruitment strategies employed by perpetrators, identifies the platforms most commonly used, and assesses their impact on victims, the majority of whom are minors. Additionally, the study briefly examines the legal challenges and protective measures required to prevent these crimes. The findings emphasize the need for stricter regulations and the implementation of awareness campaigns involving both young people and their families.
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