  The year 2020 will be remembered for two events of global significance: the
COVID-19 pandemic and 2020 U.S. Presidential Election. In this chapter, we
summarize recent studies using large public Twitter data sets on these issues.
We have three primary objectives. First, we delineate epistemological and
practical considerations when combining the traditions of computational
research and social science research. A sensible balance should be struck when
the stakes are high between advancing social theory and concrete, timely
reporting of ongoing events. We additionally comment on the computational
challenges of gleaning insight from large amounts of social media data. Second,
we characterize the role of social bots in social media manipulation around the
discourse on the COVID-19 pandemic and 2020 U.S. Presidential Election. Third,
we compare results from 2020 to prior years to note that, although bot accounts
still contribute to the emergence of echo-chambers, there is a transition from
state-sponsored campaigns to domestically emergent sources of distortion.
Furthermore, issues of public health can be confounded by political
orientation, especially from localized communities of actors who spread
misinformation. We conclude that automation and social media manipulation pose
issues to a healthy and democratic discourse, precisely because they distort
representation of pluralism within the public sphere.
