Dataset of Real OR Fake Jobs
Dataset Description
[Real or Fake] : Fake Job Description Prediction
This dataset contains 18K job descriptions out of which about 800 are fake. The data consists of both textual information and meta-information about the jobs. The dataset can be used to create classification models which can learn the job descriptions which are fraudulent.
Data Dictionary
| Coulmns | Description |
|---|---|
| job_id | Unique Job ID |
| title | The title of the job ad entry |
| location | Geographical location of the job ad |
| department | Corporate department (e.g. sales) |
| salary_range | Indicative salary range (e.g. $50,000-$60,000) |
| company_profile | A brief company description |
| description | The details description of the job ad |
| requirements | Enlisted requirements for the job opening |
| benefits | Enlisted offered benefits by the employer |
| telecommuting | True for telecommuting positions |
| has_company_logo | True if company logo is present |
| has_questions | True if screening questions are present |
| employment_type | Full-type, Part-time, Contract, etc |
| required_experience | Executive, Entry level, Intern, etc |
| required_education | Doctorate, Master’s Degree, Bachelor, etc |
| industry | Automotive, IT, Health care, Real estate, etc |
| function | Consulting, Engineering, Research, Sales etc |
| fraudulent | target - Classification attribute |
Inspiration
The dataset is very valuable as it can be used to answer the following questions:
- Create a classification model that uses text data features and meta-features and predict which job description are fraudulent or real.
- Identify key traits/features (words, entities, phrases) of job descriptions which are fraudulent in nature.
- Run a contextual embedding model to identify the most similar job descriptions.
- Perform Exploratory Data Analysis on the dataset to identify interesting insights from this dataset.
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