TikTok Search Recommendations: Governance and Research Challenges

TL;DR

This paper discusses TikTok's new search recommendation feature, highlighting governance challenges, lack of transparency, and the need for research to understand and regulate these recommendations effectively.

Contribution

It identifies key governance and transparency issues in TikTok's search recommendations and proposes a research agenda to address these challenges.

Findings

Preliminary qualitative analysis reveals governance concerns.

Lack of transparency in recommendation algorithms.

Calls for increased transparency and research access.

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.