Skip to main content

What Money Can Do: Examining the Effects of Rewards on Online Romance Fraudsters’ Deceptive Strategies

Dickinson, T. ; Wang, F. ; Maimon, D. (2023) — Deviant Behavior

View Original Source (opens in a new tab)

DOI: 10.1080/01639625.2023.2197547 (opens in a new tab)

Type:   Journal Article
Country:   United States
Tags:   Deception Strategies, Email Experiment, Financial Reward, Interpersonal Deception, Rational Choice, Romance Scams, Thematic Content Analysis
Citation tools
Download RIS Download BibTeX 


              
              

            

          

        


      

      

    

        
Transparency

        
Evidence and review status

        
This page contains AI-generated content. No human content review or subject-matter-expert review is recorded.

    


    

                    

                
Source basis

                

                    Downloaded PDF
                

            

                    

                
AI-generated page content

                

                    Yes
                

            

                    

                
Automated checks

                

                    Passed
                

            

                    

                
Administrative approval

                

                    Yes
                

            

                    

                
Human content review

                

                    Not recorded
                

            

                    

                
Subject-matter-expert review

                

                    Not recorded
                

            

            


    

        
            How this was prepared
        
        

                            

                    
Source basis

                    

                    
RSRC downloaded and privately stored a copy of the paper for internal analysis. The PDF is not offered to viewers from this page.


                                            
    
                                                            
  • 
                                    PDF added to RSRC:
                                    
                                
    • 
                                                    

                    
                                        

                

                            

                    
AI-generated page content

                    

                    
AI-generated research notes displayed on this page: Synopsis, Identified gaps, Methods, Limitations, Future work. The paper itself is not described as AI-generated.


                                            
    
                                                            
  • 
                                    Document analysis recorded:
                                    
                                
    • 
                                                            
  • 
                                    Page record updated:
                                    
                                
    • 
                                                    

                    
                                        

                

                            

                    
Automated checks

                    

                    
The current, source-bound synopsis passed the recorded versioned publication checks.


                                            
    
                                                            
  • 
                                    Checks completed:
                                    
                                
    • 
                                                    

                    
                                            

                            
                                View passed checks (3)
                            
                            
    
                                                                    
  • Length, completeness, repetition, refusal, boilerplate, and active-markup screening
    • 
                                                                    
  • Numerical claims checked against the available source text
    • 
                                                                    
  • English-source lexical grounding check
    • 
                                                            

                        

                                        

                

                            

                    
Administrative approval

                    

                    
The record is approved for public display, but a complete historical administrator action is not recorded.


                    
                                        

                

                            

                    
Human content review

                    

                    
No human review is recorded for the AI-generated content displayed on this page.


                    
                                        

                

                            

                    
Subject-matter-expert review

                    

                    
RSRC has not recorded review of this content by a subject-matter or methods expert.


                    
                                        

                

                    

    


    

        Review-state definitions

        Found a possible error?
        Request a correction.
    



    



              

        
                  

            
Synopsis

            
This field experiment sent standardized sequential emails to 500 addresses reported on Stop-scammers.com and varied promised or delivered Amazon gift-card rewards. Ninety-four suspected active fraudsters replied, and two researchers thematically coded the exchanges. They identified seven deception strategies: self-presentation, shaping the target's identity, relationship cues, money requests, requests for identifying information, moves to off-platform communication, and interactional facilitation. Communication strategies changed repeatedly as the apparent reward changed, providing behavioral evidence that offenders adapt to perceived payoff. Some addresses may have shared an operator or been misidentified, recipients may have suspected the experiment, and the sample may not represent male-persona, cryptocurrency, or other platform-based schemes.

          

        
                  

            
Identified Gaps

            
Prior romance-fraud research primarily used victims’ accounts, leaving fraudster-derived evidence on deception strategies limited. The paper identifies a further gap in understanding whether fraudsters change tactics as perceived financial reward changes, how victims’ behaviors shape those changes, and whether interpersonal-deception processes apply to romance fraudsters.

          

        
                  

            
Methods

            
The authors scraped e-mail addresses reported on stop-scammers.com in 2020, randomly assigned 500 addresses to three experimental conditions, and sent standardized sequential e-mails posing as a potential victim. The messages varied promised and delivered Amazon gift-card rewards. The final sample comprised 94 fraudsters who replied. Using NVivo, two authors independently conducted thematic content analysis of exchanges; no coding differences were reported.

          

        
                  

            
Limitations

            
Addresses may have been controlled by the same individual; some people listed on stop-scammers.com may have been misidentified as fraudsters; and recipients may have found the initial e-mails suspicious, limiting observation of natural behavior. Generalizability is unknown because the sample may not represent fraudsters using male personas, crypto-romance schemes, or other platforms.

          

        
                  

            
Future Work

            
Future research should test whether the identified strategies and reward responses generalize to fraudsters using male personas, crypto-romance scams, and other websites or apps. It should also examine whether different scam types use distinct manipulation strategies or respond differently to changing rewards.

          

              

    
    

        
Related Research Insights

        

            See how this publication connects to RSRC's living evidence syntheses through current citations and research-topic mapping.