DETECTING FAKE JOB POSTINGS WITH MACHINE LEARNING

Volume 22 No 4 (2024)

G Mahesh Challari,E.Kotesh,A.Praveen Kumar Reddy,MD.Rayyan Ali,Anil Reddy

DOI: 10.48047/nq.2024.22.4.nq24013

Abstract

To combat fraudulent job postings on the internet, this paper proposes an automated tool utilizing machine learning-based classification techniques. Various classifiers are employed to identify fraudulent posts on the web, and the performance of these classifiers is compared to determine the most effective employment scam detection model. This tool is designed to detect fake job posts from a vast number of listings. The study considers two major types of classifiers: single classifiers and ensemble classifiers. Experimental results demonstrate that ensemble classifiers outperform single classifiers in detecting job scams.

Keywords

Employment scam detection, machine learning, classification techniques, ensemble classifiers, single classifiers, fraudulent job posts.

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