This technical report presents findings from a two-phase analysis investigating potential algorithmic bias in engagement metrics on X (formerly Twitter) by examining Elon Musk’s account against a group of prominent users and subsequently comparing Republican-leaning versus Democrat-leaning accounts. The analysis reveals a structural engagement shift around mid-July 2024, suggesting platform-level changes that influenced engagement metrics for all accounts under examination. The date at which the structural break (spike) in engagement occurs coincides with Elon Musk’s formal endorsement of Donald Trump on 13th July 2024. In Phase One, focused on Elon Musk’s account, the analysis identified a marked differential uplift across all engagement metrics (view counts, retweet counts, and favourite counts) following the detected change point. Musk’s account not only started with a higher baseline compared to the other accounts in the analysis but also received a significant additional boost post-change, indicating a potential algorithmic adjustment that preferentially enhanced visibility and interaction for Musk’s posts.In Phase Two, comparing Republican-leaning and Democrat-leaning accounts, we again observed an engagement shift around the same date, affecting all metrics. However, only view counts showed evidence of a group-specific boost, with Republican-leaning accounts exhibiting a significant post-change increase relative to Democrat-leaning accounts. This finding suggests a possible recommendation bias favouring Republican content in terms of visibility, potentially via recommendation mechanisms such as the "For You" feed. Conversely, retweet and favourite counts did not display the same group-specific boost, indicating a more balanced distribution of engagement across political alignments.Overall, the results imply that while some aspects of engagement on the platform appear to have been enhanced broadly, specific visibility advantages may have been selectively applied, raising important questions about the potential impact of algorithmic adjustments on public discourse and the ‘neutrality’ of social media platforms as information carriers.
Kevin Beaumont
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