Neutral bots probe political bias on social media

TL;DR

This study uses neutral social bots on Twitter to investigate political bias, finding no strong bias in news feeds but revealing how early connections influence user exposure and community structure based on political leaning.

Contribution

It introduces a method using neutral bots to differentiate platform-induced biases from user interaction effects on social media.

Findings

No strong evidence of political bias in news feed

Exposure depends on early connections' political leaning

Conservative accounts have more followers and interact with more automated and low-credibility content

Abstract

Social media platforms attempting to curb abuse and misinformation have been accused of political bias. We deploy neutral social bots who start following different news sources on Twitter, and track them to probe distinct biases emerging from platform mechanisms versus user interactions. We find no strong or consistent evidence of political bias in the news feed. Despite this, the news and information to which U.S. Twitter users are exposed depend strongly on the political leaning of their early connections. The interactions of conservative accounts are skewed toward the right, whereas liberal accounts are exposed to moderate content shifting their experience toward the political center. Partisan accounts, especially conservative ones, tend to receive more followers and follow more automated accounts. Conservative accounts also find themselves in denser communities and are exposed to more low-credibility content.