Newstruth Distinguish Fake and Real News Using NLP

In the modern digital era, the rapid spread of misinformation and fake news across online platforms has become a major global concern. The proliferation of false information not only misleads the public but also influences opinions, behaviours, and even political or economic outcomes. To address this issue, Natural Language Processing NLP techniques are being increasingly utilized to automatically distinguish between real and fake news. This study focuses on developing an intelligent system that analyses linguistic patterns, semantic features, and contextual cues within news articles to identify their authenticity. Using machine learning and deep learning models such as Naïve Bayes, Support Vector Machines SVM , and transformer based architectures like BERT, the proposed system learns to classify news as real or fake based on textual content. The dataset undergoes preprocessing steps including tokenization, stop word removal, stemming, and vectorization to ensure effective model training. The experimental results demonstrate that NLP driven approaches significantly improve the accuracy of fake news detection, offering a robust and automated solution to combat misinformation. This research contributes to the development of reliable fact verification tools that enhance digital media integrity and promote trustworthy information dissemination. Dr. Srinivasa Reddy Kurukuntla | Adupala Sathwik Reddy | Bandla Bhavana | Chintha Saketh Pavan | Bantu Sairam | Chikati Kiran "Newstruth: Distinguish Fake and Real News Using NLP" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-10 | Issue-1 , February 2026, URL: https://www.ijtsrd.com/papers/ijtsrd100157.pdf Paper URL: https://www.ijtsrd.com/other-scientific-research-area/other/100157/newstruth-distinguish-fake-and-real-news-using-nlp/dr-srinivasa-reddy-kurukuntla