FAKE NEWS ABOUT COVID-19 ON YOUTUBE: A case study on published content about vaccines and early treatment
Fake News; Conspiracy Theory; Online Social Networks; Misinformation.
The research analyzes the content about vaccines and about the recommendation for early treatment found in YouTube videos and measures the reach of this information within the platform. As a theoretical basis, references were used about fake news, conspiracy theories, and how cognitive biases operate. and how cognitive biases operate for the assimilation of this type of content. content. To understand the digital environment and how the architecture of the dissemination of false information, we used the concepts of the echo chamber effect and the concepts of echo chamber effect and bubble filters. Structuring the dissertation are the network analysis and the content analysis, so that the content analysis so that the contents could be categorized and content could be categorized and studied in depth, especially when false information about early treatment and vaccines was identified. The data scraping was performed by means of an automated process, as well as the visualization of engagement and performance within YouTube.