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June 26, 2025

Using TikTok could be making you more politically polarized, new study finds

Credit: Pixabay/CC0 Public Domain
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Credit: Pixabay/CC0 Public Domain

People on TikTok tend to follow accounts that align with their own political beliefs, meaning the platform is creating political echo chambers among its users. These findings, from a study my collaborators, and , published in the academic journal , show that people mostly hear from voices they already agree with.

We analyzed the structure of different political networks on TikTok and found that right-leaning communities are more isolated from other and from mainstream news outlets. Looking at their , the right-leaning communities are more tightly connected than their left-leaning counterparts. In other words, conservative TikTok users tend to stick together. They rarely follow accounts with opposing views or mainstream media accounts. Liberal users, on the other hand, are more likely to follow a mix of accounts, including those they might disagree with.

Our study is based on a massive dataset of over 16 million TikTok videos from more than 160,000 public accounts between 2019 and 2023. We saw a spike of political TikTok videos during the 2020 U.S. presidential election. More importantly, people aren't just passively watching political content; they're actively creating political content themselves.

Some people are more outspoken about politics than others. We found that users with stronger political leanings and those who get more likes and comments on their videos are more motivated to keep posting. This shows the power of partisanship, but also the power of TikTok's social rewards system. Engagement signals—likes, shares, comments—are like a fuel, encouraging users to create even more.

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Why it matters

People are turning to TikTok not just for a good laugh. A recent shows that almost 40% of U.S. adults under 30 regularly get news on TikTok. The question becomes what kind of news are they watching, and what does that mean for how they engage with politics.

The content on TikTok often comes from creators and influencers or . The quality of this news content remains uncertain. Without access to balanced, fact-based information, people may struggle to make informed political decisions.

Amid the debates over , our study highlights how TikTok can be a double-edged sword in political communication. It's encouraging to see people participate in politics through TikTok when that's their medium of choice. However, if a user's network is closed and homogeneous and their expression serves as in-group validation, it may further solidify the political echo chamber.

When people are exposed to one-sided messages, it can increase hostility toward outgroups. In the long run, relying on TikTok as a source for political information might deepen people's political views and contribute to .

What other research is being done

Echo chambers have been widely studied on platforms like , but similar research on TikTok is in its infancy. TikTok is drawing scrutiny, particularly its role in , and .

TikTok has its unique format, algorithmic curation and entertainment-driven design. I believe that its function as a tool for political communication calls for closer examination.

What's next

In 2024, the and campaigns joined TikTok to reach young voters. My research team is now analyzing how these dynamics may have shifted during the 2024 election. Future research could use experiments to explore whether these campaign videos significantly influence voters' perceptions and behaviors.

Journal information: New Media & Society

Provided by The Conversation

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Get Instant Summarized Text (GIST)

TikTok users tend to follow accounts that match their political views, creating echo chambers and increasing polarization. Right-leaning communities are more isolated and tightly connected than left-leaning ones, which are more open to diverse views. Engagement features like likes and comments further motivate partisan content creation, potentially deepening political divides.

This summary was automatically generated using LLM.