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“It Felt Real” Victim Perspectives on Platform Design and Longer-Running Scams

Jingjia Xiao ; Qing Xiao ; Hong Shen (2025) — arXiv preprint v1, 2025-10-03

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DOI: 10.48550/arxiv.2510.02680 (opens in a new tab)

Country:   China
Tags:   Algorithmic Recommendations, China, Fake Trading Interfaces, Longer Running Scams, Online Scam Victims, Pig Butchering, Platform Design, Romance Scams
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Synopsis

            
This publication investigates how longer-running scams, such as romance fraud and pig-butchering, are embedded in and enabled by digital platform design. The authors ask how platform affordances and architectures—beyond individual vulnerabilities or detection tools—shape the access, trust-building, and persistence of scams. Their empirical work centers on 25 victims in China who experienced longer-running scams, using semi-structured interviews conducted over extended conversations to elicit narratives of exposure, engagement, and withdrawal. The study presents a three-layer, socio-technical model of scam progression. First, victims are exposed to scams through mainstream platform mechanisms, with recommendation feeds, search results, and community spaces amplifying visibility and lowering initial suspicion. Second, scammers fabricate legitimacy by exploiting design elements such as counterfeit trading interfaces, embedded payments, customer service chats, and aesthetically credible profiles, creating a credible appearance that resembles legitimate platforms. Third, scams are sustained through relational maintenance within social spaces—group dynamics, emotional support, and perceived social consequences of leaving—which heighten commitment and make disengagement difficult. The authors argue that platform features do not merely host scams but actively structure exposure, trust, and persistence, turning platform infrastructures into environments where deception thrives. Limitations noted include the China-specific sample and retrospective self-reports, with cautions about generalizability and the absence of direct access to scammers or platform data. The authors call for design and governance approaches that treat safety as an architectural principle of platforms, aiming to disrupt the multi-layered progression from exposure to entrapment rather than relying solely on user education or post hoc warnings.

          

        
                  

            
Identified Gaps

            
The paper identifies limited systematic analysis of how scammers exploit platform affordances across both initial access and trust-building. Prior work emphasizes user vulnerabilities, education, and detection more than platforms’ role in enabling scams. The authors also note insufficient understanding of how platform features make vulnerable groups reachable and how platform design may exacerbate inequality.

          

        
                  

            
Methods

            
The study used qualitative semi-structured interviews with 25 self-identified longer-running scam victims in China, including five pilot interviews and 20 formal interviews. Interviews lasted 60–90 minutes and addressed exposure, trust development, platform features, exit barriers, and prevention. Researchers transcribed interviews, analyzed about 350,000 Chinese words and 150-plus interaction images using reflexive thematic analysis, iteratively coded transcripts in NVivo, and triangulated accounts with screenshots and transaction records.

          

        
                  

            
Limitations

            
The sample comprises 25 victims in China, so findings may not generalize to other regions or platform ecosystems. Evidence relies mainly on retrospective victim accounts and may be affected by memory bias or post-hoc rationalization, despite supporting screenshots and transaction records. The study lacks access to scammers and internal platform detection or moderation data. Its qualitative design cannot estimate prevalence or test intervention effectiveness.

          

        
                  

            
Future Work

            
Conduct comparative research across cultural and regulatory contexts, especially in the Global South. Triangulate victim accounts with platform audits, law-enforcement cases, and computational analyses of scam-content circulation. Include scammers and platform detection/moderation perspectives through partnerships. Use longitudinal experiments or mixed methods to test staged interventions, including algorithmic risk prompts, trust-friction designs, and community-exit support.

          

              

    
    

        
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