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An exploration of the motivations of catfish perpetrators and the emotions and feelings expressed by catfish victims using automated linguistic analysis and thematic analysis

Samuel Ryan ; Jacqui Taylor (2024) — Discover Data

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DOI: 10.1007/s44248-024-00011-5 (opens in a new tab)

Type:   Journal Article
Country:   Global
Tags:   AI-Enabled Fraud, Catfishing, Emotional Impact, Financial Gain, Offender Tactics, Online Deception, Quora, Victim Experience
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Synopsis

            
This article reports a study that aims to understand why people engage in catfishing and how victims describe their emotional experiences. The researchers sought to identify perpetrators’ motivations and the emotions reported by those who were catfished, using data derived from Quora answers about catfishing. They employed two analytic approaches: thematic analysis to identify patterns in participants’ descriptions, and automated linguistic analysis (LIWC-2022) to quantify language features. The data were collected from publicly available posts on three Quora threads, yielding 6,981 words for motivations and 28,422 words for emotions, drawn from 13 motivation texts and 41-45 emotion-related texts after refinement. The study identified four motivation themes: entertainment, emulating an ideal self, desire for meaningful interaction, and financial gain. Entertainment emerged as the most prominent motive, described as a source of humor or boredom, sometimes starting in youth. Emulating an ideal self reflected insecurities about appearance and admiration for others deemed more attractive. The desire for meaningful interaction pointed to a wish for friendship or connection beyond real-life social skills, while financial gain encompassed requests for money and other exploitive tactics, sometimes evolving from initial non-financial motives. On the affective side, six victim-emotion themes were found: suspicion, love, depression, anger, embarrassment, and a sense of stupidity or naivety. Victims reported lingering negative affect, self-blame, heartbreak, and distress extending beyond the period of deception. Methodologically, LIWC analysis suggested participants’ text tended to be personal and consistent in language style across cases, though limitations included anonymity and the absence of demographic data. The authors note that LIWC does not capture full contextual nuance and that online self-reports may include fiction or exaggeration. They propose further research, including interviews, to validate and extend these findings.

          

        
                  

            
Identified Gaps

            
Catfishing-specific research remains underexplored. Earlier work emphasized demographic and psychological predictors but did not detail motivations, vulnerabilities, or effects. Research on online romance scams and dating apps does not explain all forms of catfishing across platforms. Prior studies typically assess feelings after disclosure rather than emotions before and during the experience. The authors also identify limited evidence on self-blame, pre-catfishing vulnerabilities, perpetration onset age, and persistence after victims become suspicious.

          

        
                  

            
Methods

            
The study analyzed public, anonymous English-language Quora answers from catfishing-related threads. It used 13 texts (6,981 words) about perceived perpetrator motivations and 41 victim-experience texts (28,422 words after exclusions). Researchers conducted separate inductive semantic thematic analyses following Braun and Clarke and automated LIWC-2022 analyses of analytic thinking, authenticity, and emotional tone. A language-style-matching test compared writing similarity between participant texts. The study had institutional ethics approval and removed names from quoted material.

          

        
                  

            
Limitations

            
Because Quora posts were anonymous and public, the researchers could not verify that accounts were truthful, non-fictional, or not exaggerated. Anonymity also prevented collection of age and gender data, limiting contextual interpretation of perpetrator and victim characteristics. Internet-based data may be selectively biased. LIWC results are indicative and relative rather than statistically significant, and its algorithm does not capture context, such as sarcasm or how a word is used.

          

        
                  

            
Future Work

            
Conduct in-depth research on catfishing motivations and emotional impacts to test whether these findings replicate. Interview people who have catfished to examine motivations directly. Recruit catfishing victims for a survey to test the identified emotional experiences. Measure the prevalence of vulnerabilities before catfishing, explore why victims continue despite suspicion, and collect age and gender details in future Quora studies. Artificial intelligence may help address LIWC's limited contextual interpretation.

          

              

    
    

        
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