Psycholinguistic Markers of COVID-19 Conspiracy Tweets and Predictors of Tweet Dissemination.

The adoption of conspiracy theories about COVID-19 has been fairly widespread among the general public and associated with the rejection of self-protective behaviors. Despite their significance, however, a gap remains in our understanding of the underlying characteristics of messages used to disseminate COVID-19 conspiracies. We used the construct of resonance as a framework to examine a sample of more than 1.8 million posts to Twitter about COVID-19 made between April and June 2020. Our analyses focused on the psycholinguistic properties that distinguish conspiracy theory tweets from other COVID-19 topics and predict their spread. COVID-19 conspiracy tweets were distinct and most likely to resonate when they provided explanations and expressed negative emotions. The results highlight the sensemaking functions served by conspiracy tweets in response to the profound upheaval caused by the pandemic.

Cognitive and Cultural Factors That Affect General Vaccination and COVID-19 Vaccination Attitudes.

The development of COVID-19 vaccines is a major scientific accomplishment that has armed communities worldwide with powerful epidemic control tools. Yet, COVID-19 vaccination efforts in the US have been marred by persistent vaccine hesitancy. We used survey methodology to explore the impact of different cognitive and cultural factors on the public's general vaccination attitudes, attitudes towards COVID-19 vaccines, and COVID-19 vaccination status. The factors include information literacy, science literacy, attitudes towards science, interpersonal trust, public health trust, political ideology, and religiosity. The analysis suggests that attitudes towards vaccination are influenced by a multitude of factors that operate in a complex manner. General vaccination attitude was most affected by attitudes towards science and public health trust and to a lesser degree by information literacy, science literacy, and religiosity. Attitudes towards COVID-19 vaccines were most affected by public health trust and to a lesser extent by general trust, ideology and attitudes towards science. Vaccination status was most influenced by public health trust. Possible mediating effects of correlated variables in the model need to be further explored. The study underscores the importance of understanding the relationship between public health trust, literacies, and sociocultural factors.

Public responses to COVID-19 mask mandates: examining pro and anti-Mask anger in tweets before and after state-level mandates

Governmental mandates requiring mask wearing in public spaces to slow the spread of the COVID-19 virus have been controversial in the United States. We test theory related to anger and anger expression in the context of posts about masks appearing on Twitter during a 12-week period in which mask mandates were adopted in 18 states. The results were consistent with an appraisal of mandates as providing protection from harm. Pro-mask anger directed at others for not wearing masks increased following the imposition of mandates among tweets originating from states with a mandate. In states without a mandate, pro-mask anger similarly increased over time as additional state mandates were adopted across the country. [ FROM AUTHOR] Copyright of Communication Monographs is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Informatics Approaches for Recognition, Management, and Prevention of Occupational Respiratory Disease.

Computer and information systems can improve occupational respiratory disease prevention and surveillance by providing efficient resources for patients, workers, clinicians, and public health practitioners. Advances include interlinking electronic health records, autocoding surveillance data, clinical decision support systems, and social media applications for acquiring and disseminating information. Obstacles to advances include inflexible hierarchical coding schemes, inadequate occupational health electronic health record systems, and inadequate public focus on occupational respiratory disease. Potentially transformative approaches include machine learning, natural language processing, and improved ontologies.