Online Content Consumption: Social Endorsements, Observational Learning and Word-of-Mouth

The consumption of online content can occur through observational learning (OL) whereby consumers follow previous consumers’ choices or social endorsement (SE) wherein consumers receive content sharing from their social ties. As users consume content, they also generate post-consumption word-of-mouth (WOM) signals. OL, SE and WOM together shape the diffusion of the content. This study examines the drivers of SE and the effect of SE on content consumption and post-consumption WOM. In particular, we compare SE with OL. Using a random sample of 8,945 new videos posted on YouTube, we collected a multi-platform dataset consisting of data on video consumption and WOM from YouTube and data on tweet sharing of the video from Twitter. Applying a panel vector autoregression (PVAR) model, we find that OL increases consumption significantly more than SE in the short run. However, SE has a stronger effect on content consumption in the long run. This can be attributed to the impact of SE on WOM signals, which also increase content consumption. While OL and SE leads to similar amount of positive WOM, SE generates significantly more negative WOM than OL. Our results also show that SE is driven by WOM (i.e., likes and dislikes) but not content popularity. We further confirm the effects of OL vs. SE on content consumption and WOM using a randomized experiment at the individual consumer level. Implications for content providers and social media platforms are derived accordingly