Cyber scams, a subset of cybercrimes, have increased globally, posing significant threats to individuals and communities. These scams often result in financial and psychological damages. Cyber scams are fraudulent activities conducted online, leading to financial loss and emotional distress for victims. Common types include phishing (fraudulent emails seeking personal information), identity theft, online shopping scams, investment scams, romance scams, and tech support scams. Impacts range from direct financial losses, psychological trauma, and identity theft consequences, to broader social implications like erosion of trust in digital platforms. Prevention involves awareness, secure online practices, regular monitoring of accounts, verification of information sources, and prompt reporting of suspicious activities. Previous research has indicated mixed results concerning demographic factors influencing scam susceptibility. This study aims to comprehensively analyze these factors, including age, gender, education level, marital status, employment status, income level, financial situation, ethnicity, addiction, and social engagement. Methodology: The study employed a quantitative approach, administering a structured questionnaire to 300 participants, comprising both Singapore residents and non-residents. The methodology focused on Pearson’s chi-square and Spearman’s correlation tests to analyze the relationships between demographic factors, social engagement, and scam victimization. Results: The study’s findings indicate a significant correlation between gender and scam victimization, with males showing higher susceptibility to investment-related scams. However, other demographic factors did not show a significant correlation with scam victimization. Additionally, the research found that social engagement does not significantly correlate with scam victimization, challenging previously held notions. Conclusion: This research contributes to understanding cyber scam victimization by highlighting the importance of demographic factors and social engagement. It underscores the need for multifaceted approaches in prevention and intervention strategies tailored to address the specific risks faced by different demographic groups. The study’s focus on Singapore limits its generalizability. Future research should explore these patterns in different cultural and geographical contexts and consider other variables like technological savviness and specific online behaviors.
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