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Online Romance Scammers

Lauren R. Shapiro (2022) — Cyberpredators and Their Prey

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DOI: 10.4324/9781003092292-2 (opens in a new tab)

Type:   Book Chapter
Country:   United States
Tags:   AI-Enabled Fraud, Catfishing, Financial Fraud, Identity Theft, Machine Learning, Online Dating, Romance Scams, Sextortion
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Synopsis

            
This book chapter presents online romance scams as cyber-enabled imposter and advance-fee fraud that may be committed by an individual or a coordinated group, usually for financial gain. It is an overview rather than a reported original study. The chapter is organized around definitions, typical offenders and victims, offender motives and methods, laws used in prosecution, harms to victims and society, and cybersecurity responses. That structure supports a broad introduction to the crime, but the accessible publisher preview does not identify a sample, analytic method, or empirical results. Claims beyond the chapter's stated scope therefore should not be inferred from this synopsis.

          

        
                  

            
Identified Gaps

            
Key evidence gaps include substantial underreporting, because law enforcement is reportedly uninvolved in 75%–80% of cases; uncertainty about the proportion of offenders located in the United States versus elsewhere; and an unknown number of victims who experience the optional stage involving coercion into crimes. These gaps limit prevalence estimates, offender-location knowledge, and understanding of severe exploitation pathways.

          

        
                  

            
Methods

            
This is a narrative, practice-oriented book chapter that synthesizes cited academic studies, government and law-enforcement reports, complaint statistics, legal statutes, and prosecution case examples. It describes scam definitions, offender tactics, victim patterns, harms, U.S. legal remedies, and cybersecurity detection guidance. It also summarizes prior profile-analysis research, including machine-learning and natural-language-processing findings.

          

        
                  

            
Limitations

            
The chapter appears to be a secondary-source synthesis rather than a primary empirical study. It does not report a systematic search strategy, inclusion criteria, sampling procedure, or independent statistical analysis. Many prevalence, offender, and victim claims rely on prior reports and cited studies, while complaint data are affected by substantial nonreporting. Some descriptions of typical offenders and victims may therefore be context-dependent rather than universally representative.

          

        
                  

            
Future Work

            
Future research should quantify the unknown prevalence of victims who reach the optional coercion-and-accomplice stage, improve estimates obscured by nonreporting, and evaluate whether profile-based machine-learning and reverse-image-search guidance prevent victimization. Cross-national research could also establish the geographic distribution of offenders, which the chapter states is difficult to determine.

          

              

    
    

        
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