Social Media Engagement in Two Governmental Schemes during the COVID-19 Pandemic in Macao

COVID-19 and Masking Disparities: Qualitative Analysis of Trust on the CDC's Facebook Page

This exploratory paper examines individual levels of risk assessment as impacting institutional trust in the CDC while also contributing to disparities in expressed willingness to mask early in the COVID-19 pandemic. Using both content and thematic analysis of the CDC's Facebook (FB) page from April 2020 and Gidden's modern risk society theory, I consider how social media (SM) users retrospectively perceived a dramatic change in public health (PH) advisory-from the CDC advising against masking in February 2020 (Time 1) to advising the use of "do-it-yourself" (DIY) cloth masking in April 2020 (Time 2)-through a lens of prior, self-guided research. Expressed "knowledge" of masking as preventative (or not) yielded unwavering and sometimes increasing distrust in the CDC based on user perception of the "correct" advisory, regardless of the CDC's position at Time 1 or Time 2. Simultaneously, disparities in masking behaviors appeared to be driven not by CDC guidance but by this same self-guided research. I show this via three themes: (1) claims of ineffectiveness for DIY masking (do not trust CDC now-no masking from the start); (2) conflict between the first and second CDC advisories on masking (do not trust CDC-either already masking anyway or will now); (3) disappointed in the CDC for length of time taken to make a DIY mask recommendation (do not trust CDC-either already masking anyway or will mask now). I discuss the imperative nature of two-way engagement with SM users by PH rather than using SM as a one-way mode of advisory dissemination. This and other recommendations may decrease disparities in preventative behaviors based on individual-level risk assessment as well as increase institutional trust and transparency.

COVID-19 and Public Health: Analysis of Opinions in Social Media

The article presents the results of research of public opinion during the third wave of the COVID-19 pandemic in Russia. The study touches on the attitude of citizens to public health, as well as the reaction of social media users to government measures in a crisis situation during a pandemic. Special attention is paid to the phenomenon of infodemic and methods of detecting cases of the spread of false and unverified information about diseases. The article demonstrates the application of an interdisciplinary approach using network analysis of texts and sociological research. A model for detecting social stress in the textual communication of social network users using a specially trained neural network and linguistic analysis methods is presented. The validity and validity of the results of the analysis of social network data were verified using a sociological survey. This approach allows us to identify points of tension in matters of public health promotion, during crisis situations to improve interaction between the government and society, and to timely adjust government plans and actions to ensure resilience in emergency situations for public health purposes.