A Data-driven Study of View Duration on YouTube

TL;DR

This study analyzes YouTube view duration using two datasets, revealing that engagement metrics like likes and comments significantly predict how long users watch videos, offering deeper insights into online video consumption.

Contribution

It introduces a data-driven analysis linking collective preferences and reactions to individual view durations on YouTube, enhancing understanding of user engagement.

Findings

View duration correlates positively with view count and likes per view.

Negative sentiment in comments is associated with longer view durations.

Engagement metrics can predict individual viewing times effectively.

Abstract

Video watching had emerged as one of the most frequent media activities on the Internet. Yet, little is known about how users watch online video. Using two distinct YouTube datasets, a set of random YouTube videos crawled from the Web and a set of videos watched by participants tracked by a Chrome extension, we examine whether and how indicators of collective preferences and reactions are associated with view duration of videos. We show that video view duration is positively associated with the video's view count, the number of likes per view, and the negative sentiment in the comments. These metrics and reactions have a significant predictive power over the duration the video is watched by individuals. Our findings provide a more precise understandings of user engagement with video content in social media beyond view count.