• Dr. Ikvinderpal SIngh
• Indu Bala

The rapid growth of social media platforms has revolutionized the way information is disseminated and consumed. However, this growth has also given rise to the spread of bogus news, which can have detrimental effects on individuals, organizations, and society as a whole. This research paper proposes a deep learning system that aims to detect and analyze fake news in a hybrid data environment encompassing various social media platforms. By leveraging the power of deep learning algorithms, the system aims to enhance the accuracy and efficiency of identifying and understanding bogus news.

Deep Learning; Fake news; Social media; Convolutional NN; Recurrent NN; Transformers;

"Deep Learning System to Detect and Analyze Bogus News from Hybrid Data Environment on Social Media Platforms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 2, page no.f868-f874, February-2023, Available :http://www.jetir.org/papers/JETIR2302594.pdf

"Deep Learning System to Detect and Analyze Bogus News from Hybrid Data Environment on Social Media Platforms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 2, page no. ppf868-f874, February-2023, Available at : http://www.jetir.org/papers/JETIR2302594.pdf