TikTok is a major force among social media platforms with over a billion monthly active users worldwide and 170 million in the United States. The platform's status as a key news source, particularly among younger demographics, raises concerns about its potential influence on politics in the U.S. and globally. Despite these concerns, there is scant research investigating TikTok's recommendation algorithm for political biases. We fill this gap by conducting 323 independent algorithmic audit experiments testing partisan content recommendations in the lead-up to the 2024 U.S. presidential elections. Specifically, we create hundreds of "sock puppet" TikTok accounts in Texas, New York, and Georgia, seeding them with varying partisan content and collecting algorithmic content recommendations for each of them. Collectively, these accounts viewed ~394,000 videos from April 30th to November 11th, 2024, which we label for political and partisan content. Our analysis reveals significant asymmetries in content distribution: Republican-seeded accounts received ~11.8% more party-aligned recommendations compared to their Democratic-seeded counterparts, and Democratic-seeded accounts were exposed to ~7.5% more opposite-party recommendations on average. These asymmetries exist across all three states and persist when accounting for video- and channel-level engagement metrics such as likes, views, shares, comments, and followers, and are driven primarily by negative partisanship content. Our findings provide insights into the inner workings of TikTok's recommendation algorithm during a critical election period, raising fundamental questions about platform neutrality.

翻译：TikTok作为全球月活跃用户超10亿、美国用户达1.7亿的主流社交媒体平台，已成为年轻群体获取新闻信息的关键渠道，这引发了人们对其可能影响美国乃至全球政治格局的担忧。尽管存在这些担忧，目前针对TikTok推荐算法政治偏向性的实证研究仍十分有限。为填补这一空白，我们在2024年美国总统选举前夕进行了323项独立的算法审计实验，专门测试其党派内容推荐机制。具体而言，我们在德克萨斯州、纽约州和佐治亚州创建了数百个"傀儡"TikTok账户，为这些账户注入不同党派倾向的初始内容，并系统收集每个账户获得的算法推荐内容。在2024年4月30日至11月11日期间，这些账户累计观看了约39.4万条视频，我们对所有视频进行了政治立场与党派属性的标注分析。研究发现存在显著的内容分布不对称性：相较于民主党倾向的初始账户，共和党倾向账户获得的本党派对齐内容推荐量平均高出约11.8%；而民主党倾向账户接收到的对立党派内容平均多出约7.5%。这种不对称现象在三个州均持续存在，即便在控制视频点赞量、观看量、分享量、评论数和频道粉丝数等参与度指标后依然显著，且主要由负面党派性内容驱动。本研究揭示了关键选举期间TikTok推荐算法的内部运作机制，对平台中立性这一根本问题提出了重要质疑。