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@article{174740,
        author = {Mrs G.S.Geethamani and Mr P.Logesh and MrA.Maheshwaran and MrM.kavinesan},
        title = {Enhanced Fake News Detection with the aid of  Improved Spider Monkey Optimization-based   optimal Feature Selection and Deep Neural Network},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {1774-1776},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174740},
        abstract = {Fake news has become a significant problem in recent years, leading to widespread misinformation and public manipulation. This research focuses on developing an effective fake news detection model using advanced machine learning and deep learning techniques. Existing methodologies face challenges such as poor performance with large datasets, noise, and limited generalization. The proposed solution integrates pre-processing, feature extraction, optimal feature selection via Spider Monkey Optimization (SMO), and a deep neural network (OAFDNN) with optimized activation functions. The model's performance will be validated using publicly available datasets and analyzed through various evaluation metrics. This study aims to enhance the accuracy, precision, and detection of fake news.},
        keywords = {Spider Monkey Optimization (SMO), Deep Neural Network (DNN), Fake news detection (FND), Social media, Text classification.},
        month = {April},
        }