9th Biennial ACSPRI Social Science Methodology Conference

Social media platforms such as Twitter/X and Reddit are increasingly important for political communication: opinion leaders and influencers use social media for one-to-many communication, but these spaces also enable ordinary citizens to form opinions by engaging in one-to-one discussion about social and political issues. It is important to understand how social media are facilitating or impeding political deliberation, a process whereby individuals with differing perspectives and opinions engage in discussion, potentially revising their opinions upon hearing the arguments of others.

In this presentation, I outline research into political deliberation on Twitter, conducted as part of the Volkswagen Foundation-funded “Bots Building Bridges (3B)” project. We first used a set of debate- and election-related hashtags to undertake a collection of tweets authored during the first 2020 US presidential debate. We then used the v2 Twitter API to collect the wider Twitter conversations that these tweets were part of, so our final dataset also included debate-related tweets that did not feature the target hashtags. The resulting dataset consists of over 13K reply tree network with a “conversation starter” tweet as the root node and all the subsequent replies and replies-to-replies.

I then present some preliminary findings regarding the deliberative nature of Twitter activity during the first debate, focusing on two types of analysis. First we construct a measure of deliberation involving the depth (proxy for argumentation) and breadth (proxy for representation) of reply tree networks. Second, we construct a random sample of root-to-leaf reply chains extracted from the reply trees, with the chains then manually coded for agreement, conflict, and incivility. An overall aim is to understand how deliberation trajectories vary with topics of discussion and the partisanship of the discussion partners.