This dataset is a custom-built text classification dataset for detecting fraud risk in internship and entry-level job postings. This dataset is created for an embeddings-based classifier that helps students evaluate whether internship and entry-level job postings may be legitimate, suspicious, or fraudulent.
## Dataset Summary
The dataset contains job posting texts labeled into three risk categories:
- `legitimate`: postings that look like normal internship or entry-level job advertisements
- `suspicious`: postings with warning signs such as vague requirements, missing company information, remote-only work, unclear application process, or unrealistic opportunity language
- `fraudulent`: postings originally labeled as fraudulent in the source dataset
The final dataset contains 900 examples: 300 legitimate, 300 suspicious, and 300 fraudulent job postings.
## Source Data
This dataset was adopted from the Kaggle public dataset: Real / Fake Job Posting Prediction dataset, which is ba…
