Fake Job Detection using Logistic Regression

Abstract

Fake job scams have become a big problem in recent years, costing many job searchers money and causing them emotional anguish. In order to overcome this difficulty, we present a Fake Job Detection system that can identify if job advertising is authentic or fraudulent. The system categorizes job posts into real and fraudulent categories by using machine learning techniques to evaluate job descriptions. Results from experiments show that the model does a good job of detecting bogus listings. This strategy can help job seekers focus on legitimate career prospects and steer clear of frauds.