Technologically enabled crime has proliferated in recent years. One such crime type is the live streaming of child sexual abuse (CSA). This study employs a machine learning approach to better understand the characteristics of Australians who engaged with known facilitators of CSA live streaming in the Philippines.
This model demonstrated notable success in identifying the individuals who would engage in a high number of transactions with known facilitators.
Individuals engaged in high-volume live streaming typically spent small amounts (under $55) at intervals of less than 20 days. Where prolific offenders had a criminal record, it was unlikely to consist of high-harm crime types, such as violent or sexual offences.
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