Citation
Abstract
The online romance scam is a cybercrime that has resulted in substantial impact on victims, both psychologically and financially. The display of a personal advertisement by scammers on online dating websites in the form of the user profile is often the first step in the scam strategy to attract potential victims. This study examined differences in the use of language in self- and desired partner-description found in both the scammer profiles and a set of general user profiles on online dating websites. Using a corpus-based methodology, 500 user profiles identified as having fraudulent characteristics were compared with the same number of user profiles downloaded from five popular dating portals. Words that are statistically different in their frequencies of occurrence in the two sets of data were generated using a corpus analysis software and then categorized based on semantic and contextual criteria. The analysis uncovered linguistic features that are distinctive of the scammer profiles, revealing strategies used by online scammers in constructing and engaging a certain type of victim, by intensively invoking love, romance and commitment, and conjuring hope of a future as a couple through pertinent use of lexical and function words. Implications of the study include its contribution to the understanding and identification of the linguistic indicators of romance fraud user profiles which are important in efforts to raise public awareness and for future development of computerized scam detection tools.
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Official URL or Download Paper: https://link.springer.com/article/10.1057/s41300-0...
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Modern Language and Communication |
DOI Number: | https://doi.org/10.1057/s41300-022-00169-7 |
Publisher: | Palgrave Macmillan |
Keywords: | Applied linguistics; Corpus analysis; Dating profiles; Ideal victim; Keyword analysis; Linguistic features; Online romance scam |
Depositing User: | Mr. Mohamad Syahrul Nizam Md Ishak |
Date Deposited: | 28 Jun 2024 09:08 |
Last Modified: | 28 Jun 2024 09:08 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1057/s41300-022-00169-7 |
URI: | http://psasir.upm.edu.my/id/eprint/103158 |
Statistic Details: | View Download Statistic |
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