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1. On the relationship between conspiracy theory beliefs, misinformation, and vaccine hesitancy

   https://doi.org/10.1371/journal.pone.0276082  

   Enders, Adam M. ; Uscinski, Joseph ; Klofstad, Casey ; Stoler, Justin ( October 2022 , PLOS ONE)

   Jonason, Peter Karl (Ed.)

   At the time of writing, nearly one hundred published studies demonstrate that beliefs in COVID-19 conspiracy theories and misinformation are negatively associated with COVID-19 preventive behaviors. These correlational findings are often interpreted as evidence that beliefs in conspiracy theories and misinformation are exogenous factors that shape human behavior, such as forgoing vaccination. This interpretation has motivated researchers to develop methods for “prebunking,” “debunking,” or otherwise limiting the spread of conspiracy theories and misinformation online. However, the robust literatures on conspiracy theory beliefs, health behaviors, and media effects lead us to question whether beliefs in conspiracy theories and misinformation should be treated as exogenous to vaccine hesitancy and refusal. Employing U.S. survey data (n = 2,065) from July 2021, we show that beliefs in COVID-19 conspiracy theories and misinformation are not only related to COVID-19 vaccine hesitancy and refusal, but also strongly associated with the same psychological, social, and political motivations theorized to drive COVID-19 vaccine hesitancy and refusal. These findings suggest that beliefs in conspiracy theories and misinformation might not always be an exogenous cause, but rather a manifestation of the same factors that lead to vaccine hesitancy and refusal. We conclude by encouraging researchers to carefully consider modeling choices and imploring practitioners to refocus on the worldviews, personality traits, and political orientations that underlie both health-related behaviors and beliefs in conspiracy theories and misinformation. 

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2. COVID-19: Social Media Sources of Authority During a Global Pandemic

   https://doi.org/10.1007/978-3-030-77685-5_23  

   Alsoubai, A. ( July 2021 , the Proceedings of the 21st International Conference on Human-Computer Interaction (HCII 2021))

   null (Ed.)

   Since the start of coronavirus disease 2019 (COVID-19) pandemic, social media platforms have been filled with discussions about the global health crisis. Meanwhile, the World Health Organization (WHO) has highlighted the importance of seeking credible sources of information on social media regarding COVID-19. In this study, we conducted an in-depth analysis of Twitter posts about COVID-19 during the early days of the COVID-19 pandemic to identify influential sources of COVID-19 information and understand the characteristics of these sources. We identified influential accounts based on an information diffusion network representing the interactions of Twitter users who discussed COVID-19 in the United States over a 24-h period. The network analysis revealed 11 influential accounts that we categorized as: 1) political authorities (elected government officials), 2) news organizations, and 3) personal accounts. Our findings showed that while verified accounts with a large following tended to be the most influential users, smaller personal accounts also emerged as influencers. Our analysis revealed that other users often interacted with influential accounts in response to news about COVID-19 cases and strongly contested political arguments received the most interactions overall. These findings suggest that political polarization was a major factor in COVID-19 information diffusion. We discussed the implications of political polarization on social media for COVID-19 communication. 

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3. Situating Engineering Education in a World Impacted by COVID-19

   De Pree, Thomas ; Appelhans, Sarah ; Cheville, Alan ; Akera, Atsushi ; Shuey, Melissa ( July 2021 , ASEE annual conference exposition)

   null (Ed.)

   In June 2020, at the annual conference of the American Society for Engineering Education (ASEE), which was held entirely online due to the impacts of COVID-19 (SARS-CoV-2), engineering education researchers and social justice scholars diagnosed the spread of two diseases in the United States: COVID-19 and racism. During a virtual workshop (T614A) titled, “Using Power, Privilege, and Intersectionality as Lenses to Understand our Experiences and Begin to Disrupt and Dismantle Oppressive Structures Within Academia,” Drs. Nadia Kellam, Vanessa Svihla, Donna Riley, Alice Pawley, Kelly Cross, Susannah Davis, and Jay Pembridge presented what we might call a pathological analysis of institutionalized racism and various other “isms.” In order to address the intersecting impacts of this double pandemic, they prescribed counter practices and protocols of anti-racism, and strategies against other oppressive “isms” in academia. At the beginning of the virtual workshop, the presenters were pleasantly surprised to see that they had around a hundred attendees. Did the online format of the ASEE conference afford broader exposure of the workshop? Did recent uprising of Black Lives Matter (BLM) protests across the country, and internationally, generate broader interest in their topic? Whatever the case, at a time when an in-person conference could not be convened without compromising public health safety, ASEE’s virtual conference platform, furnished by Pathable and supplemented by Zoom, made possible the broader social impacts of Dr. Svihla’s land acknowledgement of the unceded Indigenous lands from which she was presenting. Svihla attempted to go beyond a hollow gesture by including a hyperlink in her slides to a COVID-19 relief fund for the Navajo Nation, and encouraged attendees to make a donation as they copied and pasted the link in the Zoom Chat. Dr. Cross’s statement that you are either a racist or an anti-racist at this point also promised broader social impacts in the context of the virtual workshop. You could feel the intensity of the BLM social movements and the broader political climate in the tone of the presenters’ voices. The mobilizing masses on the streets resonated with a cutting-edge of social justice research and education at the ASEE virtual conference. COVID-19 has both exacerbated and made more obvious the unevenness and inequities in our educational practices, processes, and infrastructures. This paper is an extension of a broader collaborative research project that accounts for how an exceptional group of engineering educators have taken this opportunity to socially broaden their curricula to include not just public health matters, but also contemporary political and social movements. Engineering educators for change and advocates for social justice quickly recognized the affordances of diverse forms of digital technologies, and the possibilities of broadening their impact through educational practices and infrastructures of inclusion, openness, and accessibility. They are makers of what Gary Downy calls “scalable scholarship”—projects in support of marginalized epistemologies that can be scaled up from ideation to practice in ways that unsettle and displace the dominant epistemological paradigm of engineering education.[1] This paper is a work in progress. It marks the beginning of a much lengthier project that documents the key positionality of engineering educators for change, and how they are socially situated in places where they can connect social movements with industrial transitions, and participate in the production of “undone sciences” that address “a structured absence that emerges from relations of inequality.”[2] In this paper, we offer a brief glimpse into ethnographic data we collected virtually through interviews, participant observation, and digital archiving from March 2019 to August 2019, during the initial impacts of COVID-19 in the United States. The collaborative research that undergirds this paper is ongoing, and what is presented here is a rough and early articulation of ideas and research findings that have begun to emerge through our engagement with engineering educators for change. This paper begins by introducing an image concept that will guide our analysis of how, in this historical moment, forms of social and racial justice are finding their way into the practices of engineering educators through slight changes in pedagogical techniques in response the debilitating impacts of the pandemic. Conceptually, we are interested in how small and subtle changes in learning conditions can socially broaden the impact of engineering educators for change. After introducing the image concept that guides this work, we will briefly discuss methodology and offer background information about the project. Next, we discuss literature that revolves around the question, what is engineering education for? Finally, we introduce the notion of situating engineering education and give readers a brief glimpse into our ethnographic data. The conclusion will indicate future directions for writing, research, and intervention. 

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4. Understanding the Use of Images to Spread COVID-19 Misinformation on Twitter

   https://doi.org/10.1145/3579542  

   Wang, Yuping ; Ling, Chen ; Stringhini, Gianluca ( April 2023 , Proceedings of the ACM on Human-Computer Interaction)

   While COVID-19 text misinformation has already been investigated by various scholars, fewer research efforts have been devoted to characterizing and understanding COVID-19 misinformation that is carried out through visuals like photographs and memes. In this paper, we present a mixed-method analysis of image-based COVID-19 misinformation in 2020 on Twitter. We deploy a computational pipeline to identify COVID-19 related tweets, download the images contained in them, and group together visually similar images. We then develop a codebook to characterize COVID-19 misinformation and manually label images as misinformation or not. Finally, we perform a quantitative analysis of tweets containing COVID-19 misinformation images. We identify five types of COVID-19 misinformation, from a wrong understanding of the threat severity of COVID-19 to the promotion of fake cures and conspiracy theories. We also find that tweets containing COVID-19 misinformation images do not receive more interactions than baseline tweets with random images posted by the same set of users. As for temporal properties, COVID-19 misinformation images are shared for longer periods of time than non-misinformation ones, as well as have longer burst times. %\ywi added "have'' %\ywFor RQ2, we compare non-misinformation images instead of random images, and so it is not a direct comparison. When looking at the users sharing COVID-19 misinformation images on Twitter from the perspective of their political leanings, we find that pro-Democrat and pro-Republican users share a similar amount of tweets containing misleading or false COVID-19 images. However, the types of images that they share are different: while pro-Democrat users focus on misleading claims about the Trump administration's response to the pandemic, as well as often sharing manipulated images intended as satire, pro-Republican users often promote hydroxychloroquine, an ineffective medicine against COVID-19, as well as conspiracy theories about the origin of the virus. Our analysis sets a basis for better understanding COVID-19 misinformation images on social media and the nuances in effectively moderate them. 

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5. Psychosocial Effects of the COVID-19 Pandemic: Large-scale Quasi-Experimental Study on Social Media

   https://doi.org/10.2196/22600  

   Saha, Koustuv ; Torous, John ; Caine, Eric D ; De Choudhury, Munmun ( January 2020 , Journal of Medical Internet Research)

   null (Ed.)

   Background The COVID-19 pandemic has caused several disruptions in personal and collective lives worldwide. The uncertainties surrounding the pandemic have also led to multifaceted mental health concerns, which can be exacerbated with precautionary measures such as social distancing and self-quarantining, as well as societal impacts such as economic downturn and job loss. Despite noting this as a “mental health tsunami”, the psychological effects of the COVID-19 crisis remain unexplored at scale. Consequently, public health stakeholders are currently limited in identifying ways to provide timely and tailored support during these circumstances. Objective Our study aims to provide insights regarding people’s psychosocial concerns during the COVID-19 pandemic by leveraging social media data. We aim to study the temporal and linguistic changes in symptomatic mental health and support expressions in the pandemic context. Methods We obtained about 60 million Twitter streaming posts originating from the United States from March 24 to May 24, 2020, and compared these with about 40 million posts from a comparable period in 2019 to attribute the effect of COVID-19 on people’s social media self-disclosure. Using these data sets, we studied people’s self-disclosure on social media in terms of symptomatic mental health concerns and expressions of support. We employed transfer learning classifiers that identified the social media language indicative of mental health outcomes (anxiety, depression, stress, and suicidal ideation) and support (emotional and informational support). We then examined the changes in psychosocial expressions over time and language, comparing the 2020 and 2019 data sets. Results We found that all of the examined psychosocial expressions have significantly increased during the COVID-19 crisis—mental health symptomatic expressions have increased by about 14%, and support expressions have increased by about 5%, both thematically related to COVID-19. We also observed a steady decline and eventual plateauing in these expressions during the COVID-19 pandemic, which may have been due to habituation or due to supportive policy measures enacted during this period. Our language analyses highlighted that people express concerns that are specific to and contextually related to the COVID-19 crisis. Conclusions We studied the psychosocial effects of the COVID-19 crisis by using social media data from 2020, finding that people’s mental health symptomatic and support expressions significantly increased during the COVID-19 period as compared to similar data from 2019. However, this effect gradually lessened over time, suggesting that people adapted to the circumstances and their “new normal.” Our linguistic analyses revealed that people expressed mental health concerns regarding personal and professional challenges, health care and precautionary measures, and pandemic-related awareness. This study shows the potential to provide insights to mental health care and stakeholders and policy makers in planning and implementing measures to mitigate mental health risks amid the health crisis. 

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