A new study suggests YouTube’s recommendation algorithm may be shaping political perspectives differently for men and women – even when both groups start with the same interest in political content. The research, published in Cornell University’s arXiv repository, explored how YouTube’s recommendation system responds to different viewing behaviors.

Researchers created 160 automated social bots, splitting them into two groups with “male-coded” and “female-coded” viewing habits. While both sets of accounts showed identical interest in YouTube’s News & Politics category, their recommendations reportedly evolved in dramatically different directions over time.

Different algorithms, different political experiences

To conduct the experiment, researchers programmed 80 bots with viewing habits associated with traditionally male-oriented content, such as gaming and sports. Another 80 bots were assigned habits linked to female-oriented content, including fashion, lifestyle, and vlog videos.

Each account then completed 150 consecutive interaction sessions, allowing researchers to monitor how YouTube’s recommendation engine responded.

The results suggested that male-coded accounts were more frequently directed toward confrontational and politically charged topics such as crime, law enforcement, immigration, and defense-related issues. These accounts were also reportedly shown more content linked to powerful state institutions like Immigration and Customs Enforcement (ICE) and the Department of Justice.

Female-coded accounts, meanwhile, encountered a broader mix of political content that leaned toward international affairs, culture, arts, and lifestyle-related policy discussions. Researchers also found that these accounts received more politically neutral recommendations overall.

Perhaps more notably, the study claimed that male-coded profiles became trapped inside tighter recommendation loops, repeatedly encountering overlapping videos that reinforced similar viewpoints. Female-coded accounts experienced a more varied and less concentrated information ecosystem.

Why the findings matter

YouTube remains one of the world’s largest content platforms and an increasingly influential source of news and political information. During the 2020 US election cycle, for example, political campaigns heavily invested in YouTube advertising to influence voters and shape narratives online.

However, the new study shifts attention away from paid promotions and toward the platform’s recommendation engine itself – the system that decides what users watch next. Jonathan Gray, codirector of the Center for Digital Culture at King’s College London, said the findings contribute to growing concerns surrounding algorithm-driven political influence and online radicalization. Gray argued that recommendation systems remain largely opaque despite their enormous societal impact.

The research also adds to broader debates about whether large tech platforms unintentionally amplify polarization by creating personalized echo chambers around users. As scrutiny surrounding AI-driven recommendation systems intensifies globally, studies like this may increase pressure on platforms such as YouTube to provide greater transparency into how their algorithms shape public discourse and political behavior.