  Optimism about the Internet's potential to bring the world together has been
tempered by concerns about its role in inflaming the 'culture wars'. Via mass
selection into like-minded groups, online society may be becoming more
fragmented and polarized, particularly with respect to partisan differences.
However, our ability to measure the social makeup of online communities, and in
turn understand the social organization of online platforms, is limited by the
pseudonymous, unstructured, and large-scale nature of digital discussion. We
develop a neural embedding methodology to quantify the positioning of online
communities along social dimensions by leveraging large-scale patterns of
aggregate behaviour. Applying our methodology to 5.1B Reddit comments made in
10K communities over 14 years, we measure how the macroscale community
structure is organized with respect to age, gender, and U.S. political
partisanship. Examining political content, we find Reddit underwent a
significant polarization event around the 2016 U.S. presidential election, and
remained highly polarized for years afterward. Contrary to conventional wisdom,
however, individual-level polarization is rare; the system-level shift in 2016
was disproportionately driven by the arrival of new and newly political users.
Political polarization on Reddit is unrelated to previous activity on the
platform, and is instead temporally aligned with external events. We also
observe a stark ideological asymmetry, with the sharp increase in 2016 being
entirely attributable to changes in right-wing activity. Our methodology is
broadly applicable to the study of online interaction, and our findings have
implications for the design of online platforms, understanding the social
contexts of online behaviour, and quantifying the dynamics and mechanisms of
online polarization.
