AI-Based Detection of Fake Internship and Job Offers for College Students Using NLP and Machine Learning

The rapid expansion of online job portals, social media platforms, and messaging applications has made it easier

for college students to access internship and job opportunities. However, this convenience has also led to a significant rise

in fraudulent offers targeting students. These fake opportunities often attract candidates by promising high salaries,

guaranteed placements, or easy hiring processes, while secretly aiming to collect registration fees or sensitive personal

information.Due to limited awareness and the absence of effective verification mechanisms, many students fall victim to

such scams. Traditional methods of verifying job authenticity are often manual, time-consuming, and unreliable. To

address this issue, this study proposes an AI-based detection system that leverages Natural Language Processing (NLP)

techniques to analyze the textual content of job and internship offers.The proposed system aims to automatically classify

opportunities as genuine or fraudulent based on linguistic patterns, keywords, and contextual analysis. By implementing

machine learning models trained on real-world datasets, this approach enhances accuracy and reduces human effort in

identifying scams. Ultimately, this system seeks to provide a reliable and efficient solution to safeguard students from

deceptive job offers and support them in making informed career decisions.