Characterization of Misinformation Dynamics in COVID-19 related health information in online social media

Abstract:Social media has become predominant as a source of information for many health care consumers. Howeverfalse and misleading information are a pervasive problem in this context. Specifically, during CVID-19 pandemic,misinformation has been a significant public health challenge, impeding the effectiveness of public healthawareness campaigns and resulting in suboptimal responsiveness to the communication of legitimate risk-related information. In the proposed research, we will apply our "Pragmatics to Reveal Intent in Social Media(PRISM) framework to facilitate automated detection of intent and belief attributes underlying COVID-19 relatedmisinformation. The PRISM framework aims to incorporate and integrate communication intent, semantics andstructure of online communication to study social processes and cognitive factors underlying misinformationcomprehension. Such analysis forms the foundational step towards characterization of misinformation seedingand perception in digital social settings, ultimately allowing us to develop scalable and reliable computationalinfrastructure that can help formulate resilient and effective dissemination approaches to negotiatemisinformation spread, easing public health burden and informing policy regulations as needed.