TikTok US Spin-off Sale: Algorithm Control, Content Curation, and Implications for US Users

Tederal analyst Kelly Cotter discusses the proposed TikTok sale to a majority American-owned entity, creating a US-only app and licensing the platform’s core algorithm for retraining. The conversation highlights how the algorithm shapes what users see, the potential influence of investors with political leanings on content and guidelines, and what differences a US-centric data set could introduce for Americans. The discussion also touches on how the platform’s short-video format, features like stitches, and watch-time signals affect content ranking and user engagement, and what shifts might occur if ownership changes outcomes and audience behavior.

Overview of the TikTok Sale

The podcast examines a proposed TikTok sale that would spin off a US-only version of the app with majority American ownership (about 80%), while Chinese investors through ByteDance-owned Dance would own less than 20%. The central driver for the deal concerns national security and control, with a particular focus on the platform’s algorithm, which would be licensed to the new US company and retrained for US-only users. This structural change raises questions about how ownership and governance could influence what content is promoted or suppressed, and how such shifts might reshape the platform’s cultural footprint.

“The deal is going to create a new US only app spun off from the original app, that it's going to be a majority ownership by American companies,” - Kelly Cotter, Assistant Professor, Pennsylvania State University.

How TikTok’s Algorithm Works

The algorithm sits at the heart of the platform, tailoring feeds to individual preferences by interpreting signals from user behavior such as likes, shares, and watch time. Short video formats may provide clearer signals about what users care about, enabling precise content ranking. Features like stitches and shared sounds foster cross-user connections that can reveal evolving interests and trends. While the algorithm is not unique in principle, TikTok's implementation is perceived as highly effective at keeping users engaged.

“The algorithm is at the heart of everything that TikTok does,” - Kelly Cotter.

Investor Influence and Content Impacts

Attention centers on who will own and influence the US app. Oracle is a notable player in related TikTok data operations in the US, and several named investors have ties to conservative political circles. The discussion considers how such investors might influence the algorithm’s curation and the platform’s community guidelines, potentially altering what content is deemed acceptable or effective for engagement. The possibility of ideological tilt in the US app raises concerns about content diversity and the portrayal of sensitive topics.

“Investors have ties to the Trump administration and could tweak the algorithm and guidelines,” - Kelly Cotter.

US-Only App and Data Context

With a US-only user base, retraining the licensed TikTok algorithm on a US data set could shift content norms toward American values and behaviors. While global content remains accessible to all users, the US app’s feed would be shaped by a data subset that reflects American usage patterns. The conversation also considers how user migration might occur if perceptions of ideological alignment or content shifts drive some audiences away, potentially altering the platform’s overall balance of content and creators.

“If investors exert influence on the app, we might see subtle shifts in the kinds of content that appear,” - Kelly Cotter.

Context for Public Understanding

The discussion underscores that people often recognize that feeds are filtered by algorithms but may not grasp the broader societal implications of these processes. The for-you feed is designed to optimize engagement, yet the social consequences of algorithmic curation—especially under different ownership structures—remain a critical field of inquiry for governance and literacy initiatives.

“People are often aware of how algorithms affect their own encounters, but not the broader societal impacts,” - Kelly Cotter.

Terminology and Takeaways

Key terms include for-you algorithm, content moderation, community guidelines, retraining, data localization, and platform governance. The podcast highlights the tension between enabling personalized experiences and ensuring fair, diverse, and safe discourse across changing ownership landscapes.