Recommender systems (RS) on platforms like YouTube are often evaluated as if they operate in a closed environment. In practice, however, user consumption patterns are also shaped by a broader ecosystem of external sources. This paper investigates how external link interactions influence RS behavior. We conducted a controlled experiment with three intervention timings and found that a single external link exerts an immediate and significant impact on YouTube’s recommendations, an influence that decays but persists over time. These findings contribute to our understanding of how external interactions shape RS outputs and their subsequent impact on content diversity.

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Influencing YouTube Recommendations Through Shared Links

  • Adriano C. L. Mourthé,
  • Evelin Amorim,
  • Carlos E. Mello,
  • Alípio Jorge

摘要

Recommender systems (RS) on platforms like YouTube are often evaluated as if they operate in a closed environment. In practice, however, user consumption patterns are also shaped by a broader ecosystem of external sources. This paper investigates how external link interactions influence RS behavior. We conducted a controlled experiment with three intervention timings and found that a single external link exerts an immediate and significant impact on YouTube’s recommendations, an influence that decays but persists over time. These findings contribute to our understanding of how external interactions shape RS outputs and their subsequent impact on content diversity.