In the absence of clear, consistent guidelines about the COVID-19 pandemic in the United States, many people use social media to learn about the virus, public health directives, vaccine distribution, and other health information. As people individually sift through a flood of information online, they collectively curate a small set of accounts, known as crowdsourced elites, that receive disproportionate attention for their COVID-19 content. However, these elites are not all created equal: not all accounts have received the same attention during the pandemic, and various demographic and ideological groups have crowdsourced their own elites. Using a mixed-methods approach with a panel of Twitter users in the United States over the first year of the COVID-19 pandemic, we identify COVID-19 crowdsourced elites. We distinguish sustained amplification from episodic amplification and demonstrate that crowdsourced elites vary across demographics with respect to race, geography, and political alignment. Specifically, we show that different subpopulations preferentially amplify elites that are demographically similar to them, and that they crowdsource different types of elite accounts, such as journalists, elected officials, and medical professionals, in different proportions. In light of this variation, we discuss the potential for using the disproportionate online voice of crowdsourced COVID-19 elites to equitably promote public health information and mitigate misinformation across networked publics.

Populism, as many have observed, is a communication phenomenon as much as a coherent ideology whose mass appeal stems from the fiery articulation of core positions, notably hostility toward “others,” bias against elites in favor of “the people,” and the transgressive delivery of those messages. Yet much of what we know about populist communication is based on analysis of candidate pronouncements, the verbal message conveyed at political events and over social media, rather than transgressive performances—the visual and tonal markers of outrage—that give populism its distinctive flair. The present study addresses this gap in the literature by using detailed verbal, tonal, and nonverbal coding of the first US presidential debate of 2016 between Donald Trump and Hillary Clinton to show how Trump’s transgressive style—his violation of normative boundaries, particularly those related to protocol and politeness, and open displays of frustration and anger—can be operationalized from a communication standpoint and used in statistical modeling to predict the volume of Twitter response to both candidates during the debate. Our findings support the view that Trump’s norm-violating transgressive style, a type of political performance, resonated with viewers significantly more than Clinton’s more controlled approach and garnered Trump substantial second-screen attention.

The Russian-sponsored Internet Research Agency’s (IRA) use of social media to influence U.S. political discourse is undoubtedly troubling. However, scholarly attention has focused on social media, overlooking the role that news media within the country played in amplifying false, foreign messages. In this article, we examine articles in the U.S. news media system that quoted IRA tweets through the lens of changing journalism practices in the hybrid media system, focusing specifically on news gatekeepers’ use of tweets as vox populi. We find that a majority of the IRA tweets embedded in the news were vox populi. That is, IRA tweets were quoted (1) for their opinion, (2) as coming from everyday Twitter users, and (3) with a collection of other tweets holistically representing public sentiment. These findings raise concerns about how modern gatekeeping practices, transformed due to the hybrid media system, may also unintentionally let in unwanted disinformation from malicious actors.

This study investigates how successful Russian Internet Research Agency (IRA) Twitter accounts constructed the followings that were central to their disinformation campaigns around the 2016 U.S. presidential election. Treating an account’s social media following as both an ego network and an audience critical for information diffusion and influence accrual, we situate IRA Twitter accounts’ accumulation of followers in the ideologically polarized, attention driven, and asymmetric political communication system. Results show that partisan enclaves on Twitter contributed to IRA accounts’ followings through retweeting; and that mainstream and hyperpartisan media assisted conservative IRA accounts’ following gain by embedding their tweets in news. These results illustrate how network dynamics within social media and news media amplification beyond it together boosted social media followings. Our results also highlight the dynamics fanning the flames of disinformation: partisan polarization, media fragmentation and asymmetry, and an attention economy optimized for engagement rather than accuracy.

As an integral component of public discourse, Twitter is among the main data sources for scholarship in this area. However, there is much that scholars do not know about the basic mechanisms of public discourse on Twitter, including the prevalence of various modes of communication, the types of posts users make, the engagement those posts receive, or how these things vary with user demographics and across different topical events. This paper broadens our understanding of these aspects of public discourse. We focus on the first nine months of 2020, studying that period as a whole and giving particular attention to two monumentally important topics of that time: the Black Lives Matter movement and the COVID-19 pandemic. Leveraging a panel of 1.6 million Twitter accounts matched to U.S. voting records, we examine the demographics, activity, and engagement of 800,000 American adults who collectively posted nearly 300 million tweets during this time span. We find notable variation in user activity and engagement, in terms of modality (e.g., retweets vs. replies), demographic subgroup, and topical context. We further find that while Twitter can best be understood as a collection of interconnected publics, neither topical nor demographic variation perfectly encapsulates the "Twitter public." Rather, Twitter publics are fluid, contextual communities which form around salient topics and are informed by demographic identities. Together, this paper presents a disaggregated, multifaceted description of the demographics, activity, and engagement of American Twitter users in 2020.