On YouTube Search API Use in Research

Abstract

YouTube is among the most widely-used platforms worldwide, and has seen a lot of recent academic attention. Despite its popularity and the number of studies conducted on it, much less is understood about the way in which YouTube's Data API, and especially the Search endpoint, operates. In this paper, we analyze the API's behavior by running identical queries across a period of 12 weeks. Our findings show that the search endpoint returns highly variable results between queries. Specifically, the API seems to randomize returned videos based on the relative popularity of the respective topic during the query period, making it nearly impossible to obtain representative historical video samples, especially during non-peak topical periods. Our results also suggest that the API may prioritize shorter, more popular videos, although the role of channel popularity is not as clear. We conclude with suggested strategies for researchers using the API for data collection, as well as future research directions on expanding the API's use-cases.