Rabble-Rousers in the New King's Court: Algorithmic Effects on Account Visibility in Pre-X Twitter

TL;DR

This study examines how Twitter's algorithmic feed during Elon Musk's ownership favored certain behaviors and account types, revealing biases that influence account visibility and online discourse health.

Contribution

It uncovers that account visibility biases are driven more by behavioral patterns and platform interactions than political affiliation, expanding understanding of algorithmic effects.

Findings

Right-leaning accounts gained more exposure due to behavior, not politics.

Verified accounts received less exposure in algorithmic feeds.

Platform interactions, like attention from Elon Musk, influenced account visibility.

Abstract

Algorithmic effects on social media platforms have come under recent scrutiny, with several studies reporting that right-leaning accounts tend to receive more exposure. In this paper, we expand upon this body of work using data collected from user feeds after Twitter's change of ownership but before its re-branding to X. We replicate findings from prior work regarding the increased exposure of right-leaning accounts to wider audiences in algorithmically curated compared to reverse-chronological feeds, and, crucially, we further unpack this effect to illuminate what correlated (and did not correlate) with these differences. Our results reveal that right-leaning accounts benefited not necessarily due to their political affiliation, but likely because they behaved in ways associated with algorithmic rewards; namely, posting more agitating content and receiving attention from the platform's owner, Elon Musk, who was the most central network account. We also demonstrate that legacy-verified accounts, like businesses and government officials, received less exposure in the algorithmic feed compared to non-verified or Twitter Blue-verified accounts. We discuss implications of these findings for the intersection between behavioral incentives for algorithmic reach and the health of online discourse.