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Media Presentation of Online Romance Fraud in the Czech Republic: Visibility, Victim-Offender Framing, and Sentiment

Abubakari, Yushawu (2026) — European Journal on Criminal Policy and Research

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DOI: 10.1007/s10610-026-09664-1 (opens in a new tab)

Type:   Book Chapter
Country:   Czech Republic
Tags:   AI-Enabled Fraud, Content Analysis, Cybercrime, Czech Media, Czech Republic, Law Enforcement, Media Framing, Media Representation, Media Study, Media Visibility, Offender Framing, Offender Tactics, Platform Policy, Prevention, Psychology, Relational Quantitative Content Analysis, Risk Factors, Romance Scams, Sentiment, Sentiment Analysis, Victim Experience, Victim Framing, Victim Offender Framing, Victimization
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Synopsis

            
This study used relational quantitative content analysis to examine how online romance fraud is presented across major Czech news outlets, public-service media, blogs, and English-language Czech coverage. The corpus was collected with Czech and English search terms, processed with web-collection and translation tools, and anchored to official cases and police communications. Psychological harm was the most visible victim frame, appearing about 160 times per 1,000 sentences versus about 120 for financial harm; both harms co-occurred strongly with negative sentiment. Fabricated crises or urgency, impersonation, and love-bombing were the most visible offender tactics, while support-seeking had a moderate association with positive sentiment. Event-driven media selection, official-source influence, translation, and interpretive coding prevent causal or population-level conclusions.

          

        
                  

            
Identified Gaps

            
The study identifies a lack of empirical research on ORF in Central Europe, especially the Czech Republic, and a need to systematically analyze media representations, visibility, framing of victims and offenders, and sentiment over time. It notes gaps in understanding regional narratives, mechanisms, and societal impacts, calling for broader, policy-relevant analysis beyond incident reporting.

          

        
                  

            
Methods

            
The study uses Relational Quantitative Content Analysis (RQCA) of Czech media on ORF. It builds a corpus from major outlets (iDNES.cz, Česká televize, Novinky.cz, Seznam Zprávy, Český rozhlas, Blesk.cz, Expats.cz) and blogs, using Czech/English keywords. Data were collected with Immersive Translate and analyzed via MAXQDA Web Collector to map co-occurrences among concepts (victimization, offending, sentiment, policy framing) anchored to official cases, treating police communications as part of the ORF communication environment.

          

        
                  

            
Limitations

            
Limitations include reliance on publicly available media sources, which may reflect episodic, event-driven reporting and institutional agendas. Translation and coding subjectivity may affect sentiment and framing inferences. The study cannot establish causality or generalize beyond the Czech media landscape, and police/public communications may bias the corpus toward official narratives. Victim/offender perspectives are largely absent.

          

        
                  

            
Future Work

            
Key future research directions include: systematically investigating the emergence, prevalence, mechanisms, and societal impacts of online romance fraud (ORF) in Central Europe and in the Czech Republic; conducting cross-country comparative framing studies; implementing longitudinal monitoring to distinguish episodic versus continuous media coverage; linking media framing to policy, prevention, and victim-support strategies; triangulating media representations with police and court data to assess accuracy and consequences; expanding cross-platform analyses to include social media and blogs alongside traditional outlets; and refining Relational Quantitative Content Analysis (RQCA) methods for cybercrime contexts.

          

              

    
    

        
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