A Big Data ecosystem for evaluating health misinformation on social media

Infodemic

Infodemics--Digital misinformation on social media has led to harmful and costly beliefs in the general population. Notably, these beliefs have resulted in public health crises to the detriment of governments worldwide and their citizens. Consequently, there is a critical need for an expert system capable of processing vast amounts of health-related digital data to detect patterns of public health misinformation. To address this need, this research designed and developed the U-MAS, a big data pipeline and ecosystem for identifying and analyzing health misinformation on social media.

The novel U-MAS expert system offers a significant opportunity for public health officials globally to detect and analyze misleading health information. Furthermore, this approach can emphasize on integrating social media data from multiple sources into dashboards for a multiplatform analysis and testing of the ecosystem on other public health use cases. This pipeline is currently used to detect and analyze fluoride-related misinformation, vaccine hesitancy, heatwave-related misinformation, and diet misinformation, providing real-time insights into their trends.

PI: Dr. Plinio Morita; Co-PI: Dr. Zahid Butt

Project members: Irfhana Zakir Hussain, Navneet Kaur, Arlene Oetomo, Dr. Jasleen Kaur, Dr. Thokozani Hanjahanja-Phiri, Halyna Padalko, Dr. Dmytro Chumachenko

External project members:  Matheus Lotto, Bara’ AlShurman, Lisa Chen