Machine Learning Techniques for True and Fake Job Posting

Abstract

According to research, there are around 188 million unemployed people around the globe. We may find many job vacancies on job portals and across the internet to help the job seekers. India alone has more than a hundred job portals. One major issue people face here is that the job seekers are not sure if the employer is real or fake. Most of these portals do not have a system that could check if the employer posting a job is real or fake. Scammers are making use of this opportunity to post fake job offers which might look genuine to the job seekers applying for it. The poor job seekers might lose a large amount of money and time. A best possible solution for this problem would be that the job portal itself being able to identify if the job being posted is real or fake. Paper suggests using a machine learning model to achieve this goal. An idea here is to use natural language processing to understand and analyze the job posting and then making use of a machine learning model to predict if the job posting is real or fake. The first step is to import a dataset which has real life, real, and fake job posting. In this project, Employment Scam Aegean Dataset provided by University of Aegean Laboratory of Information and Communication system security is being used. Linear SVC is being used in this project for predicting real and fake job posting on a job portal.