Fake Job Postings Dataset - Replication Archive for "TabuLLM: Feature Extraction from Tabular Text Data using Large Language Models"

This dataset contains 17,880 job postings labeled as fraudulent (4.84%) or legitimate (95.16%). It is the EMSCAD (Employment Scam Aegean Dataset) originally published by Vidros et al. (2017, Future Internet, doi:10.3390/fi9010006) and distributed via Kaggle (shivamb/real-or-fake-fake-jobposting-prediction). This archive is provided for reviewers and readers of the manuscript "TabuLLM: Feature Extraction from Tabular Text Data using Large Language Models" (submitted to the Journal of Statistical Software), as a convenience mirror to support offline replication without requiring a Kaggle account. File: fake_job_postings.csv - 17,880 rows × 18 columns. Columns include 7 free-text fields (title, location, department, company_profile, description, requirements, benefits), 3 binary indicators, 5 categorical features, 1 numeric identifier (job_id), 1 sparse field (salary_range, 84% missing), and 1 binary target (fraudulent).