fake-job-detection

Chrome extension that scores job postings for likelihood of being ghost jobs.

Spot fake job and internship offers before they cost you. Spring Boot + React app that scores job posts, offer letters and screenshots for scam signs using rules, a Tribuo ML model and domain checks.

An AI-powered machine learning system that detects potentially fraudulent job postings using NLP and TF-IDF text classification.

Production-ready AI & NLP system to detect fraudulent job advertisements and recruitment scams using FastAPI, XGBoost, Optuna, MongoDB, and Prometheus/Grafana observability.

NLP-based Fake Job Posting Detection system using TF-IDF feature engineering, Linear SVM classification, and Streamlit deployment to identify fraudulent job advertisements.

A data analysis project that studies real and fake job posts to help people avoid scams and find genuine jobs.

AI-powered fake job posting detector using Random Forest, FastAPI, Streamlit, and TiDB Cloud analytics.

Fake Job Detector is a machine learning–based application designed to identify fraudulent job postings using Natural Language Processing (NLP) techniques.

An end-to-end machine learning system that detects fraudulent job postings based on textual content, metadata, and job attributes.

An AI-powered fake job detection system that uses Machine Learning and NLP to identify potentially fraudulent job postings, analyze scam risk factors, and help job seekers make safer career decisions.

AI-powered system for detecting fake job postings using machine learning, recruitment risk scoring, and LIME-based explainable AI.

NLP-based Machine Learning solution to detect fraudulent job advertisements. Features a modular pipeline from text cleaning to a Gradio/Streamlit prototype

JobShield is a full-stack, machine-learning-powered web application designed to detect fraudulent and fake job postings. It features a sleek React (Vite) frontend and a high-performance FastAPI backend that serves an XGBoost classifier trained using advanced NLP techniques (TF-IDF, spaCy) to analyze and identify scam job listings.

An AI-powered framework to detect and prevent online recruitment fraud using NLP, Machine Learning, and Deep Learning.

Explainable Fake Job Posting Detection using NLP & Machine Learning

NLP model to detect fake job postings (TF-IDF + XGBoost) with an interactive Streamlit app.

Hybrid fake job detection system combining rule-based analysis, text features, and explainability to assess suspicious job postings.

Fake Job Post Prediction — An NLP-based project to detect fake job postings using text preprocessing, feature extraction (TF-IDF), and machine learning models. The project includes data cleaning, exploratory analysis, model training, and prediction notebooks.

Machine Learning-powered web application for detecting fake job postings using NLP and classification models.

This repository contains a cleaned and combined dataset of job postings, originally collected in 2015. It is intended to be used as a baseline for research and development related to job posting analysis and fake job detection.