Sexual Offenses against Children: Social Learning Theory and Dark Web Reinforcement

As cybercrime activity increasingly uses anonymous technologies, the dramatic growth of child sexual exploitations on the dark web has posed a challenge to law enforcement agencies. Data were gathered in 2019 and 2020 through face - to - face interviews with a juvenile in New Taipei City, Taiwan. This paper extends the application of social learning theory to online child sexual abuse behavior. Research testing Akers's social learning theory has been confined to sexual offenses against children on the dark web. A social learning concept of differential association, definitions, imitation, and differential reinforcement is illustrated and supported by online child sexual abuse behavior findings. Before it occurs, preventing child sexual abuse has become a critical issue and necessary effort from all areas of society: family caring, school instruction, community-based treatment, and social values. An innovative social learning strategy to battle online child sexual abuse is proposed to reduce juvenile delinquency on the dark web. Every child, parent, teacher, or social worker who works with children should realize what child sexual abuse is and prevent it.