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Influence of User Profile Attributes on e-Cigarette-Related Searches on YouTube: Machine Learning Clustering and Classification.

Dhiraj MurthyJuhan LeeHassan DashtianGrace Kong
Published in: JMIR infodemiology (2023)
Our results indicate that demographic attributes factor into YouTube's algorithmic systems in the context of e-cigarette-related queries on YouTube. Specifically, differences in the age and sex attributes of user profiles do result in variance in both the videos presented in YouTube search results as well as in the types of these videos. We find that underage profiles were exposed to e-cigarette content despite YouTube's age-restriction policy that ostensibly prohibits certain e-cigarette content. Greater enforcement of policies to restrict youth access to e-cigarette content is needed.
Keyphrases
  • machine learning
  • smoking cessation
  • public health
  • healthcare
  • mental health
  • physical activity
  • artificial intelligence
  • young adults
  • big data
  • single cell