Mapping the Invocation Structure of Online Political Interaction

TL;DR

This paper introduces network-based methods to analyze online political interactions by constructing invocation graphs that reveal how users engage with different ideological domains, providing insights into the evolution of political discourse leading up to the 2016 US election.

Contribution

We develop a novel approach using invocation graphs to analyze the structure and evolution of political interactions on social media across the ideological spectrum.

Findings

Invocation links span increasing ideological distances over time.

Asymmetry exists between left-to-right and right-to-left interactions.

Interaction patterns changed significantly before the 2016 election.

Abstract

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.