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@article{178589,
        author = {KUMANAN S and P Pandi Deepa},
        title = {Fake/ Real News Headlines Identification Using  Real-time API Fetching System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {5381-5386},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178589},
        abstract = {In the current quick-paced digital landscape, the wide dissemination of fake news and disinformation has grown to be an important challenge. Social media sites and online news websites allow users to post whatever they want to, making it more challenging to differentiate between factual and fabricated information. Fake news can have harsh effects, determining public opinion, elections, medical choices, as well as societal stability. Hence, creating a system to identify automatically fake news is crucial in order to enhance credible information and minimize misinformation. The system is trained on a labeled dataset with both real and fake news items. It applies TF-IDF vectorization to extract significant features from the text and a Naive Bayes classifier for prediction. After the model has been trained, it will be able to scan a user-input headline and provide a judgment of whether or not it is likely real or fake. The solution aids in automating verification and provides instant, reliable outcomes. In order to enhance the system's reliability, the application is coupled with the News API that retrieves associated news articles in real-time according to the input headline of the user. This integration of machine learning with real-time data brings a solid layer of authenticity. The application is developed with Flask for web backend and HTML and CSS for frontend. Machine learning parts are developed utilizing Python libraries such as scikit-learn and pandas. The end result is a simple web interface where users can just enter the news headline and get an instant verification of its authenticity. This system can prove to be an effective weapon in the hands of journalists, students, researchers, and the common public to battle the increasing menace of false news.},
        keywords = {Fake News Detection, Machine Learning, Natural Language Processing (NLP), Real-time News Validation, News API Integration, Headline Classification, Misinformation Detection.},
        month = {May},
        }