AI-Driven Forensic Cyberpsychology Intervention Strategies for Social Media Platform and School Managers to Mitigate Cyber Fraud At-Risk Adolescents

Abstract: Adolescent cyber fraud is an escalating concern, with a 32% increase in youth-driven cybercrime between 2022 and 2024. This study employs a narrative literature review and thematic analysis to synthesize research on AI-driven forensic cyberpsychology, adolescent cyber deception, and fraud detection methodologies, following Braun and Clarke's six-phase thematic analysis framework. The findings identified validation-seeking behaviors, socioeconomic stressors, and AI-detected deception patterns as the three dominant risk factors influencing adolescent cyber deception. Empirical evidence indicates that adolescents exhibiting high levels of self-doubt and digital validation dependence are 45% more likely to engage in cyber deception, while socioeconomic stressors, particularly financial instability and low parental monitoring, increase cyber fraud susceptibility by 60%. AI-driven forensic analysis demonstrates high detection accuracy levels, identifying manipulative language cues by 82%, social engineering behaviors by 87%, and risk-based engagement patterns by 90%. This study proposes an AI-driven fraud detection strategy modeled on the Validation Syndrome Diagnostic Triangle (VSDT) framework that integrates psychological deception markers, parental monitoring levels, and social media reinforcement mechanisms, underscoring the need for AI-driven digital literacy programs, algorithmic fraud detection on social media platforms, and AI-assisted forensic cyberpsychology interventions in schools. The findings provide actionable insights for policymakers, educators, and platform managers to implement AI-driven fraud prevention strategies, ensuring early intervention and fostering digital responsibility among adolescents. Keywords: Forensic Cyberpsychology, AI-Driven Fraud Detection, Adolescent Cybercrime, Digital Literacy, Validation-Seeking Behaviors, Dark Triad Traits, Cyber Fraud Prevention, Psychological Deception Markers