Detecting cyber employment fraud in platform-based space
A multi-agent large language model approach
Bibliographic Data
| ID | 21409754 |
|---|---|
| Authors | Quan Sun (0000-0001-7402-9410), Sun Quan (Texas A&M University), Ling Wu (0000-0001-5406-6927, University of Alabama, corresponding author), Xinyue Ye (0000-0001-8838-9476, University of Alabama, corresponding author), Claire Lee (0000-0002-7557-7010, University of Massachusetts Lowell), Wei Li (0000-0002-3581-849X, Texas A&M University), Cuiling Liu (0000-0001-7646-1418, Texas A&M University) |
| Year | 2026 |
| Volume | 105 |
| Pages | 102692 |
| Publication date | 2026-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Criminal Justice (JOURNAL) |
| Journal identifiers | ISSN: 0047-2352 • E-ISSN: 1873-6203 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.jcrimjus.2026.102692 |
| OpenAlex | W7166503899 |
| Language | EN |
| References cited | 96 |
Artificial neural network · Consistency (knowledge bases) · Cybercrime · Harm · Law enforcement · Logistic regression · Multilayer perceptron · Random forest · Relation (database) · Vulnerability (computing) · Artificial Intelligence in Healthcare and Education · Cybercrime and Law Enforcement Studies · Spam and Phishing Detection
Smote
How cybercriminal communities grow and change
A machine learning approach to detecting fraudulent job types
Artificial intelligence-assisted criminal justice reporting
Information technology and Gen Z
Signal crimes and signal disorders
Cognitive processes underlying context effects in attitude measurement
Applying Routine Activity Theory to Cybercrime
| Citation velocity | historical |
|---|---|
| Highly cited | No |