Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{160304,
        author = {YAMA SAI AKSHAY and ESHWAR SUBASH and harashleen kour and BOPPANA BALA SAI},
        title = {ENROL EMAIL PROJECT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {6819-6825},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=160304},
        abstract = {Today’s globe has a serious fake news problem, so recognizing unreal news on social media platforms is crucial. The various phases involved in applying machine learning to identify bogus news. The raw data is first cleaned of extraneous information and made ready for processing. Then, using the cleansed data’s important metadata, we train a machine learning model to discern between real and false news. We test the model on fresh data after it has been trained to make sure it functions properly. The model is then used to evaluate fresh articles and categories them as real or fraudulent depending on what it has learned. However, it’s important to remember that this approach is not perfect and has limitations, but it can help us combat fake news in the digital age.},
        keywords = {Deep Learning, TFIDF, Natural Language Processing, and Machine Learning.},
        month = {March},
        }