  The share of videos in the internet traffic has been growing, therefore
understanding how videos capture attention on a global scale is also of growing
importance. Most current research focus on modeling the number of views, but we
argue that video engagement, or time spent watching is a more appropriate
measure for resource allocation problems in attention, networking, and
promotion activities. In this paper, we present a first large-scale measurement
of video-level aggregate engagement from publicly available data streams, on a
collection of 5.3 million YouTube videos published over two months in 2016. We
study a set of metrics including time and the average percentage of a video
watched. We define a new metric, relative engagement, that is calibrated
against video properties and strongly correlate with recognized notions of
quality. Moreover, we find that engagement measures of a video are stable over
time, thus separating the concerns for modeling engagement and those for
popularity -- the latter is known to be unstable over time and driven by
external promotions. We also find engagement metrics predictable from a
cold-start setup, having most of its variance explained by video context,
topics and channel information -- R2=0.77. Our observations imply several
prospective uses of engagement metrics -- choosing engaging topics for video
production, or promoting engaging videos in recommender systems.
