No abstract

One of the most recognizable aphorisms about the plight of Millennials is that we are overeducated and underpaid. The causes and effects of this have been detailed in the abstract, but for me this meant that when I joined Twitter on December 22, 2008, I was working two jobs to make my student loan payments every month. My supplemental job at a popular midrange clothing

On the afternoon of 9 August 2014, 18-year-old Michael 'Mike' Brown was shot and killed by Officer Darren Wilson in the small American city of Ferguson, Missouri. Brown's body lay in the street for four and a half hours, and during that time, his neighbors and friends took to social media to express fear, confusion, and outrage. We locate early tweets about Ferguson and the use of the hashtag #Ferguson at the center of a counterpublic network that provoked and shaped public debates about race, policing, governance, and justice. Extending theory on networked publics, we examine how everyday citizens, followed by activists and journalists, influenced the #Ferguson Twitter network with a focus on emergent counterpublic structure and discursive strategy. We stress the importance of combining quantitative and qualitative methods to identify early initiators of online dissent and story framing. We argue that initiators and their discursive contributions are often missed by methods that collapse longitudinal network data into a single snapshot rather than investigating the dynamic emergence of crowdsourced elites over time.

In this research we examine the advocacy and community building of transgender women on Twitter through methods of network and discourse analysis and the theory of networked counterpublics. By highlighting the network structure and discursive meaning-making of the #GirlsLikeUs network, we argue that the digital labor of trans women, and especially trans women of color, represents the vanguard of struggles over self-definition. We find that trans women on Twitter, led by Janet Mock and Laverne Cox, and in response to histories of misrepresentation and ongoing marginalization and violence, deliberately curate an intersectional networked counterpublic that works to legitimize and support trans identities and advocate for trans autonomy in larger publics and counterpublics.

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.