YouTube Recommendations and Effects on Sharing Across Online Social Platforms

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DOI

In January 2019, YouTube announced its platform would exclude potentially harmful content from video recommendations while allowing such videos to remain on the platform. While this step is intended to reduce YouTube's role in propagating such content, the continued availability of links to these videos in other online spaces makes it unclear whether this compromise actually reduces their spread. To assess this impact, we apply interrupted time series models to measure whether different types of YouTube sharing in Twitter and Reddit changed significantly in the eight months around YouTube's announcement. We evaluate video sharing across three curated sets of potentially harmful, anti-social content: a set of conspiracy videos that have been shown to experience reduced recommendations in YouTube, a larger set of videos posted by conspiracy-oriented channels, and a set of videos posted by alternative influence network (AIN) channels. As a control, we also evaluate effects on video sharing in a dataset of videos from mainstream news channels. Results show conspiracy-labeled and AIN videos that have evidence of YouTube's de-recommendation experience a significant decreasing trend in sharing on both Twitter and Reddit. For videos from conspiracy-oriented channels, however, we see no significant effect in Twitter but find a significant increase in the level of conspiracy-channel sharing in Reddit. For mainstream news sharing, we actually see an increase in trend on both platforms, suggesting YouTube's suppression particular content types has a targeted effect. This work therefore finds evidence that reducing exposure to anti-social videos within YouTube, without deleting these videos, has potential pro-social, cross-platform effects in sharing across the information ecosystem. At the same time, increases in the level of conspiracy-channel sharing raise concerns about how content producers are responding to YouTube's changes, and transparency from the platform is needed to evaluate these effects further.