Quantifying social organization and political polarization in online platforms
Isaac Waller, Ashton Anderson

TL;DR
This paper introduces a neural embedding method to quantify social and political polarization in online communities, revealing a significant 2016 polarization event on Reddit driven mainly by new right-wing users, with minimal individual-level polarization.
Contribution
The study develops a novel neural embedding approach to measure online community social dimensions and applies it to large-scale Reddit data to analyze polarization dynamics over 14 years.
Findings
Reddit experienced a major polarization shift around 2016.
The polarization was mainly due to new users, not existing ones.
Right-wing activity drove the ideological asymmetry.
Abstract
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.…
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