Paper Key : IRJ************016
Author: Repana Jyothi Prakash,Arockia Raj Abraham,Shaik Khizar,Kothamandi Naga Jyothi
Date Published: 06 Nov 2024
Abstract
The surge in deceptive business practices, notably exacerbated by the aftermath of the Coronavirus pandemic, has intensified financial challenges for job seekers. This study addresses the urgent need to combat fraudulent job postings by developing a robust predictive model. Utilizing a comprehensive dataset with features like textual descriptions and meta-data, the research aims to identify key indicators through thorough exploratory data analysis. Two primary questions guide the study: (RQ1) What indicators consistently flag fake job postings? (RQ2) Can a classifier, enhanced with AI techniques, accurately distinguish between real and fake job listings? By integrating advanced AI techniques, particularly natural language processing (NLP), the study contributes to the field by showcasing the effectiveness of the developed model. The findings hold the potential to empower job seekers, recruitment platforms, and regulatory bodies in the ongoing battle against business-related scams.
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