TikTok Search Recommendations: Governance and Research Challenges
Taylor Annabell, Robert Gorwa, Rebecca Scharlach, Jacob van de Kerkhof, Thales Bertaglia
TL;DR
This position paper argues that TikTok's preformulated search recommendations raise governance and transparency concerns, especially under regulatory regimes like the EU's Digital Services Act. It synthesizes qualitative observations from Dutch influencers to motivate a computational research agenda centered on how recommendations are generated, how coordination among users can manipulate them, contextual harms, and topic classification. The authors highlight data-access constraints, a dynamic and opaque interface, and the need for transparent documentation and research access to responsibly study these recommendations. The work emphasizes the sociotechnical complexities of platform-driven search and advocates cross-disciplinary collaboration to inform policy and future empirical studies across social media and search ecosystems.
Abstract
Like other social media, TikTok is embracing its use as a search engine, developing search products to steer users to produce searchable content and engage in content discovery. Their recently developed product search recommendations are preformulated search queries recommended to users on videos. However, TikTok provides limited transparency about how search recommendations are generated and moderated, despite requirements under regulatory frameworks like the European Union's Digital Services Act. By suggesting that the platform simply aggregates comments and common searches linked to videos, it sidesteps responsibility and issues that arise from contextually problematic recommendations, reigniting long-standing concerns about platform liability and moderation. This position paper addresses the novelty of search recommendations on TikTok by highlighting the challenges that this feature poses for platform governance and offering a computational research agenda, drawing on preliminary qualitative analysis. It sets out the need for transparency in platform documentation, data access and research to study search recommendations.