A Study on prevention model of the Romance Scam crime

This paper proposes a prevention model based on collecting romance-scam reports and victim cases, then classifying the material into offender, victim, message, and scenario data. Text-mining outputs would support several interventions: checking known offender information when social-media users add new contacts, pre-filtering messages with extracted keywords, and using recurring scenarios to anticipate changing approaches. The paper also argues that overseas offending, victim blaming, and misunderstanding of the word "romance" discourage reporting and complicate enforcement. The available abstract describes the model and its intended uses but does not report a dataset size, deployed system, or effectiveness evaluation, so the proposal should not be read as a validated detection tool.