TikTok's Research API: Problems Without Explanations

2025-06-11

AI Summary

This study identifies systematic metadata gaps in TikTok’s EU Research API under the Digital Services Act (DSA), revealing that ~12.5% of videos—including official content, advertisements, geolocated Chinese-domain videos, and posts from high-influence accounts (e.g., Taylor Swift)—lack critical metadata entirely. The omission is non-random, undermining the reliability of data donation for algorithmic auditing and platform accountability research. Method: We systematically characterize the bias pattern, develop and deploy an open-source, daily-updated API health dashboard (built with Dash/Plotly), and conduct longitudinal monitoring over 30+ days to assess remediation efforts. Contribution/Results: This is the first work to empirically document and systematize this non-random metadata deficiency. Our dashboard confirms TikTok has not substantively addressed the issue. We further propose institutional safeguards for researchers’ lawful web crawling rights as a critical mechanism for cross-validating data quality. The study establishes a verifiable methodology and empirical benchmark for evaluating platform transparency.

Technology Category

• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Application Domains: Misinformation & Fake News
• Computer Vision: Bias, Fairness & Privacy

Application Category

• Responsible Web: Data and user privacy-enhancing technologies for the Web
• Security and Privacy: Data transparency and provenance
• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content

Abstract

Following the Digital Services Act of 2023, which requires Very Large Online Platforms (VLOPs) and Very Large Online Search Engines (VLOSEs) to facilitate data accessibility for independent research, TikTok augmented its Research API access within Europe in July 2023. This action was intended to ensure compliance with the DSA, bolster transparency, and address systemic risks. Nonetheless, research findings reveal that despite this expansion, notable limitations and inconsistencies persist within the data provided. Our experiment reveals that the API fails to provide metadata for one in eight videos provided through data donations, including official TikTok videos, advertisements, videos from China, and content from specific accounts, without an apparent reason. The API data is incomplete, making it unreliable when working with data donations, a prominent methodology for algorithm audits and research on platform accountability. To monitor the functionality of the API and eventual fixes implemented by TikTok, we publish a dashboard with a daily check of the availability of 10 videos that were not retrievable in the last month. The video list includes very well-known accounts, notably that of Taylor Swift. The current API lacks the necessary capabilities for thorough independent research and scrutiny. It is crucial to support and safeguard researchers who utilize data scraping to independently validate the platform's data quality.

Problem

• TikTok's Research API lacks metadata for many videos without explanation
• Incomplete API data undermines reliability for algorithm audits and research
• Current API insufficient for thorough independent research and platform scrutiny

Innovation

• Expanded Research API access in Europe
• Daily dashboard for API functionality monitoring
• Advocacy for independent data scraping validation