MurkySky: Analyzing News Reliability on Bluesky

TL;DR

This paper presents MurkySky, a comprehensive analysis of news reliability on Bluesky, revealing that reliable news is prevalent but unreliable sources are more partisan and topic-specific, with a left-leaning bias.

Contribution

It introduces MurkySky, a new tool for tracking unreliable news sources on Bluesky, and provides the first detailed analysis of news reliability and source bias on the platform.

Findings

Reliable news is prevalent on Bluesky.

Unreliable sources are more partisan and left-leaning.

Unreliable content concentrates on specific topics.

Abstract

Bluesky has recently emerged as a lively competitor to Twitter/X for a platform for public discourse and news sharing. Most of the research on Bluesky so far has focused on characterizing its adoption due to migration. There has been less interest on characterizing the properties of Bluesky as a platform for news sharing and discussion, and in particular the prevalence of unreliable information on it. To fill this gap, this research provides the first comprehensive analysis of news reliability on Bluesky. We introduce MurkySky, a public tool to track the prevalence of content from unreliable news sources on Bluesky. Using firehose data from the summer of 2024, we find that on Bluesky reliable-source news content is prevalent, and largely originating from left-leaning sources. Content from unreliable news sources, while accounting for a small fraction of all news-linking posts, tends to originate from more partisan sources, but largely reflects the left-leaning skew of the platform. Analysis of the language and hashtags used in news-linking posts shows that unreliable-source content concentrates on specific topics of discussion.