Unveiling the Patterns of Romance Scams in South Korea
Choi, SW. ; Lee, J. ; Choi, YJ. (2024) — International Journal of Cyber Behavior, Psychology and Learning
Type:
Journal Article
Country:
South Korea
Synopsis (AI-Generated)
The study used triangulation: web-crawled 437 KB of publicly available Naver and YouTube news articles, videos, and blog posts using three Korean-language scam-related search terms; crime script analysis of the pre-crime and criminal-event phases; and email feedback interviews with five romance-scam investigators recruited through snowball sampling in July 2023. It produced three pre-crime scripts and 13 criminal-event scripts. KakaoTalk is a salient South Korean communication channel in these scams, reflecting its dominance in the national messaging market. Sustained manipulation, including gaslighting and confirmation bias, is described as increasing victim dependence on scammers' narratives. The analysis excluded the post-offense phase because it would require interviews with perpetrators, many of whom operate abroad.
Identified Gaps (AI-Generated)
The paper identifies limited research on romance scams in South Korea, attributed to relatively low awareness of their seriousness. It also notes that the South Korean legal framework excludes romance scams from a telecommunications-fraud law that provides account suspension, damage mitigation, and remedies. The study lacks post-offense information because perpetrator interviews are difficult when organizations operate abroad.
Methods (AI-Generated)
The study used triangulation: web-crawled 437 KB of publicly available Naver and YouTube news articles, videos, and blog posts using three Korean-language scam-related search terms; crime script analysis of the pre-crime and criminal-event phases; and email feedback interviews with five romance-scam investigators recruited through snowball sampling in July 2023. It produced three pre-crime scripts and 13 criminal-event scripts.
Limitations (AI-Generated)
The analysis excluded the post-offense phase because it would require interviews with perpetrators, many of whom operate abroad. The authors state that constraints in the current dataset restrict generalizability. Data were publicly accessible online materials supplemented by feedback from only five snowball-sampled investigators, rather than direct offender or victim interviews.
Future Work (AI-Generated)
Conduct longitudinal studies of victims’ long-term impacts. Use more diverse datasets and cross-cultural comparisons to improve applicability, identify patterns and differences, and inform more effective prevention and support strategies. Research is also needed on counterstrategies to scams using emerging technologies, including deepfakes and generative AI.
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