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@article{170773,
        author = {B.Yashwitha and K.V.Siva Prasad Reddy},
        title = {Deep Detectives with Automatic Deletion},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {7},
        pages = {2453-2458},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=170773},
        abstract = {The integrity of online information is now seriously threatened by the quick spread of fake news. An automatic deletion mechanism with a stringent 5-second time limit is incorporated into the novel architecture for fake news detection presented in this study. The system uses a combination of supervised learning algorithms that have been trained on a large dataset of verified news and fake news in order to achieve high precision in spotting bogus information. To improve detection accuracy, important criteria such language patterns, the reliability of the source, and cross-referencing with reliable databases are used. This quick reaction system is essential for stopping the spread of false information before it becomes widespread. Our tests show that the suggested approach successfully lowers the frequency of false information and restricts its exposure . In order to solve this problem, this article investigates the creation of a thorough false news detection system with the potential to delete content automatically. In order to increase detection accuracy, the system combines sophisticated machine learning (ML), deep learning models. It does this by utilizing cutting-edge structures like transformers and multimodal frameworks. We also look at how network analysis may be used to find user behavior and disinformation tendencies that frequently accompany bogus news. This method adds an automated deletion mechanism to quickly lessen the impact of false information by eliminating flagged content based on predetermined confidence criteria, whereas prior systems mainly concentrate on detection.},
        keywords = {Misinformation, Fact-Checking, Natural Language Processing, Machine Learning, Pattern Recognition, Training Data, Reporting Tools, Socia Media.},
        month = {December},
        }