Abstract: This research examines and assesses methods for detecting false news from four perspectives: the incorrect information it contains, the distribution patterns, and the source's reputation. Based on the review, the survey also identifies some prospective study subjects. We discover and explain fundamental foundational principles in a number of areas to encourage participation. Fake news is the subject of interdisciplinary research. We believe that this survey will help to facilitate collaborative efforts. To propose a solution, experts from the fields of computer and information sciences, social sciences, political science, and the media were brought together. Examine fake news to see if such efforts may improve the accuracy and efficiency of fake news identification. Most importantly, it's straightforward to understand.
Keywords: Social Media, CNN, Machine learning (ML),Deep Fake(DF);
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DOI:
10.17148/IJARCCE.2022.116135
