The Use of Social Media in Irregular Migration and Migrant Smuggling: A Qualitative Study in Türkiye
Bibliographic record
Abstract
With the advancement of digital communication technologies, social media has become a critical platform for both irregular migrants and migrant smugglers. This medium directly impacts the mobility of irregular migration, making the battle against migrant smuggling and irregular migration in cyberspace a critical issue not only at a national but also at an international scale. Therefore, understanding how smugglers use social media is a pressing research priority. This study aims to uncover the purposes and methods of social media use by irregular migrants and migrant smugglers along migration routes. The research was conducted using semi-structured interview techniques with law enforcement officials, irregular migrants under administrative detention, and migrant smugglers who have been prosecuted for migrant smuggling crimes. A total of thirty-four people were interviewed in-depth. The results indicate that migrant smugglers actively use social media to communicate with irregular migrants and organize illegal crossings. Law enforcement agencies, in turn, track these digital traces to identify smuggling networks. However, the constantly evolving methods of migrant smugglers and their use of encrypted communication remain one of the biggest challenges faced by law enforcement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".