Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Misinformation is the intentional dissemination of false or misleading information, often shared as news through social media platforms. In today's digital era, people across the globe increasingly depend on online sources for their news and information. While this convenience allows for easy access to data at any moment, it also presents challenges, particularly concerning the risks associated with information overload when untrue information is presented to the public. The phenomenon of fake news poses a significant threat due to its adverse effects on public perceptions. To address this issue, this discussion focuses on comparing computational techniques for detecting fake news in real-time articles. The process involves data mining, feature extraction, model training, and evaluation, utilizing various datasets. The methodology encompasses data preprocessing, feature extraction, and the application of model training and assessment utilizing multiple metrics, including accuracy, precision, recall, and F1-score.
"Multilingual Fake News Detection using a Machine Learning Approach", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.c446-c455, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504276.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator