Tarun Kumar 06 01 Fake news has become a significant concern in todays digital age as it can easily mislead and deceive people One of the fundamental steps to combat fake news is through fake news detection In recent years research has focused on developing effective techniques for detecting fake news using Natural Language Processing It further affects their emotions and cultural values creating a tense among people and instigating anger against fellow people or the government This further changes the order in society causing hate speeches riots strikes or even fatal accidents that affect innocent livesWhen situations like these affect society its wise that we utilize the necessary technologies in aid to eliminate this kind of issue One such tech thats disrupting human language processing is Natural Language Processing NLP which processes information like text audio etc between languages and text and audio formats Leveraging this technology to process the text and analyze the motive and sentiment could shed light on the reliability of the trueness of the text As a result of this we could develop a fake news detection system using NLPTo develop such a system we have to train the machine learning model with an existing dataset Based on the knowledge gained from this training the model would be able to identify a pattern in the test data we give Here training the model plays an important role as it affects the accuracy of the model in giving the final output This model can be evaluated by testing it with real and fake news articles We can develop a better understanding of how to detect fake newsfrom the result generated by the model and we can finetune it in order to attain a higher accuracy level These developed accuracy models can be used by others for various purposes in NLP to build better adapting models that make the life of humans easier Copyright (c) World Journal of Pharmaceutical Seiences. All rights reserved 2026