  The surge in political information, discourse, and interaction has been one
of the most important developments in social media over the past several years.
There is rich structure in the interaction among different viewpoints on the
ideological spectrum. However, we still have only a limited analytical
vocabulary for expressing the ways in which these viewpoints interact.
  In this paper, we develop network-based methods that operate on the ways in
which users share content; we construct \emph{invocation graphs} on Web domains
showing the extent to which pages from one domain are invoked by users to reply
to posts containing pages from other domains. When we locate the domains on a
political spectrum induced from the data, we obtain an embedded graph showing
how these interaction links span different distances on the spectrum. The
structure of this embedded network, and its evolution over time, helps us
derive macro-level insights about how political interaction unfolded through
2016, leading up to the US Presidential election. In particular, we find that
the domains invoked in replies spanned increasing distances on the spectrum
over the months approaching the election, and that there was clear asymmetry
between the left-to-right and right-to-left patterns of linkage.
