Male Victim

Research on "male victim" spans diverse contexts, focusing on identifying and mitigating vulnerabilities in various systems where males are targeted or harmed. Current studies employ machine learning models, including CatBoost and deep neural networks, to analyze data related to domestic violence, online harassment (e.g., harmful memes), and manipulation in reinforcement learning environments. These analyses aim to improve detection of attacks, understand underlying factors contributing to victimization, and develop strategies for intervention and prevention, ultimately contributing to a more comprehensive understanding of male victimhood across multiple domains.