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Self and desired partner descriptions in the online romance scam: a linguistic analysis of scammer and general user profiles on online dating portals

Kam-Fong Lee ; Mei Yuit Chan ; Afida Mohamad Ali (2022) — Crime Prevention and Community Safety

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DOI: 10.1057/s41300-022-00169-7 (opens in a new tab)

Type:   Journal Article
Country:   Malaysia
Tags:   AI-Enabled Fraud, Corpus Comparison, Dating Profiles, Fraud Detection, Linguistic Analysis, Offender Tactics, Prevention, Psychology, Romance Scams, Scammer Strategies, Trust Development, Victim Experience, Victim Targeting
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Synopsis

            
This study investigates how online romance scammers construct their dating profiles linguistically, comparing them with genuine users on mainstream dating platforms. The focus is on self-descriptions and desired partner descriptions to uncover patterns that differentiate scammer communication from legitimate users. The authors collected 500 verified scammer profiles from ScamDigger and compared them with 500 general profiles taken from five popular dating sites: eHarmony, OKCupid, Match, Tinder, and Dating.com. Only the narrative sections were analyzed, excluding demographic form fields. Corpus linguistics methods were applied, using AntConc software to identify statistically significant differences in word usage between the two corpora. Findings reveal that scammer profiles rely heavily on adjectives emphasizing romance, trust, and commitment. Words such as honest, loving, caring, romantic, trustworthy, faithful, passionate, and affectionate occurred far more often in scammer texts than in general user profiles. Notably, special was overwhelmingly used to describe desired partners, appealing to victims’ longing to feel unique and valued. Religious terms like god-fearing also appeared distinctively, aligning with prior studies that highlight appeals to faith as a trust-building tactic. By contrast, general user profiles referenced activities and hobbies such as travelling, food, films, yoga, books, dogs, and fashion, pointing to more varied interests and lifestyles. In terms of function words, scammers disproportionately used the copula “I am,” creating formulaic self-presentations (“I am a caring person,” “I am honest”). They also relied heavily on intensifiers like very and the future modal will, the latter used to conjure an imagined future together (“a relationship that will last forever”). This linguistic construction strongly appeals to individuals seeking committed and enduring relationships. Interestingly, scammers used first-person pronouns (I) more frequently than genuine users, contradicting prior deception research which suggested deceivers avoid self-reference. This pattern reflects the dating profile context, where projecting an appealing self is central. The study concludes that scammers deliberately foreground emotional and relational qualities to target individuals who idealize romance, commitment, and exclusivity. Such victims, often middle-aged and financially stable, are more susceptible to manipulation. By contrast, general users present broader lifestyle narratives, making scammers’ narrow emotional focus a distinguishing feature. The implications are practical as well as theoretical. Linguistic markers identified in the study can aid in public awareness training and support the development of automated detection tools that flag suspicious profiles based on overuse of emotional vocabulary, religious framing, and formulaic “I am” constructions. The findings also reinforce the idea that while scammers mimic authentic self-presentation, their profiles are systematically patterned to exploit emotional vulnerability and create an illusion of sincerity.

          

        
                  

            
Identified Gaps

            
Prior scam-stage research does not explain how scammers use language to attract and engage targets. Linguistic evidence that scammer-authored profiles depict particular target or victim types had not been sufficiently investigated. The paper also identifies a need for indicators beyond static profiles, including language from actual scammer–victim interaction.

          

        
                  

            
Methods

            
The study used an inductive corpus-comparison design. It compared narrative self- and desired-partner descriptions from 500 identified scammer dating profiles with 500 general profiles drawn from five popular dating portals. Scammer profiles came from ScamDigger; general profiles had at least 80 narrative words and included 250 stated male and 250 stated female profiles per corpus. AntConc generated statistically differentiated keywords; researchers then examined concordance contexts and manually categorized lexical and function words semantically.

          

        
                  

            
Limitations

            
Generalizability should be treated cautiously because dating portals may contain different user demographics, which were not included in the selection criteria. The general-profile set was not verified non-scammer data and could contain some scammer profiles. Gender was balanced but not analyzed as a variable because a more extended analysis was outside the paper’s scope. Findings concern narrative profile text only, excluding form-style demographic fields.

          

        
                  

            
Future Work

            
Develop additional linguistic indicators of romance-fraud communication, particularly by examining actual ongoing scammer–victim interactions to clarify how trust is gained. Develop computerized detection tools that compare test texts with generalized reference texts using established keyword-frequency thresholds, while clearly specifying ethical caveats to prevent misuse or misinterpretation.

          

              

    
    

        
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