Study: X algorithm boosts right-wing accounts during US elections

Occurred: July 2024-

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X appears to have updated its algorithm to boost its owner Elon Musk and favour right-wing accounts shortly after he declared his support for Donald Trump during the 2024 US presidential election, according to researchers.

What happened

Following Elon Musk's public endorsement of Donald Trump mid-July 2024, X's algorithm quietly began amplifying posts from Musk and other right-leaning accounts, according to Queensland University of Technology researchers.

Engagement metrics for Musk's posts surged dramatically from July 13, 2024, with view counts increasing by 138 percent and retweets by 238 percent, compared to previous levels, the researchers found.

The shift overlapped with a broader trend in which Republican-leaning accounts saw similar boosts that started around the same time, albeit to a lesser degree.

Why it happened

Musk's alignment with Trump and significant financial backing for his campaign have led to suspicions that he intentionally tweaked the platform's algorithm to enhance visibility for pro-Trump content.ย 

Many of Musk's posts during the US 2024 elections were either supportive of Trump or derogatory towards his opponent, Kamala Harris, which further fueled concerns about algorithmic bias favouring right-wing narratives.ย 

What it means

The findings suggest that X is evolving into a platform where a select group of right-wing accounts dominate discussions, potentially creating an "oligarchical" information landscape.ย 

The shift has important implications for political discourse and voter information accessibility during political elections, as users may be exposed predominantly to one ideological perspective while being deprived of diverse viewpoints.ย 

The study also highlighted how manipulation of this kind could undermine the perceived neutrality of social media platforms, raising questions about their role in shaping public discourse.

Algorithmic bias

Algorithmic bias describes systematic and repeatable errors in a computer system that create "unfair" outcomes, such as "privileging" one category over another in ways different from the intended function of the algorithm.

Source: Wikipedia ๐Ÿ”—

System ๐Ÿค–

Operator:
Developer: X Corp
Country: USA
Sector: Politics
Purpose: Recommend content
Technology: Recommendation algorithm; Machine learning
Issue: Bias/discrimination; Ethics/values; Transparency

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