Understanding Nigerian e-mail scams: A computational content analysis approach. Issue 2 (4th March 2021)

• Record Type: Journal Article
• Authors: Genc, Yegin; Kour, Harpreet; Arslan, Hasan T.; Chen, Li-Chiou
• Is Part Of: Information security journal. Volume 30:Issue 2(2021)
• Page Start: 88
• Page End: 99
• Publication Date: 2021-03-04
• Subjects: Cybercrime -- e-mail fraud -- fraud detection -- Nigerian scam -- content analysis -- topic models; Computer security -- Periodicals; Electronic data processing departments -- Security measures -- Periodicals; 005.805
• DOI: 10.1080/19393555.2020.1804647
• Languages: English
• ISSNs: 1939-3555

Abstract

ABSTRACT: e-mail scams have been around for a long time, and they are still remarkably successful. Understanding these scams can help combat fraud by raising public awareness and improving anti-fraud technologies. We conducted an in-depth analysis of e-mail contents with a mixed-method approach using machine-learning-based content analysis and qualitative analysis. We identified five stories (i.e., topics) scammers used in their e-mails. Further, we explored similarities between messages from the same scammers. Our findings suggest some scammers resend a message with the same story as before but with highly textual differences. We argue this might be a deceptive maneuver to avoid spam blockers.