New Digital Divide Shaped by Algorithm? Evidence from Agent-Based Testing on Douyin’s Health-Related Video Recommendation

Abstract

While recommendation algorithms have significantly empowered human communication process, there is an emerging scholarly and societal concern regarding the potential discrimination inherent in algorithmic decision-making. The present study employs a novel agent-based testing approach to conduct an automated audit of the Douyin algorithm’s recommendations for health-related videos, aiming to investigate its relationship with information inequalities between individuals who are socioeconomically advantaged and disadvantaged. Our findings imply the possible existence of a new digital divide, wherein the algorithm tends to recommend a smaller proportion of authenticated health-related videos on cheap phone models, representing users in low socioeconomic group. Furthermore, this divide was mitigated when both groups demonstrated the same watching strategy for authenticated information. This study implies that recommendation algorithms actively perpetuate and exacerbate discriminatory social structures in reality. We also advocate for increased attention and education among the low socioeconomic group to enhance their health information literacy and understanding of algorithmic mechanisms.

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