  Unlike popular videos, which would have already achieved high viewership
numbers by the time they are declared popular, YouTube trending videos
represent content that targets viewers attention over a relatively short time,
and has the potential of becoming popular. Despite their importance and
visibility, YouTube trending videos have not been studied or analyzed
thoroughly. In this paper, we present our findings for measuring, analyzing,
and comparing key aspects of YouTube trending videos. Our study is based on
collecting and monitoring high-resolution time-series of the viewership and
related statistics of more than 8,000 YouTube videos over an aggregate period
of nine months. Since trending videos are declared as such just several hours
after they are uploaded, we are able to analyze trending videos time-series
across critical and sufficiently-long durations of their lifecycle. In
addition, we analyze the profile of users who upload trending videos, to
potentially identify the role that these users profile plays in getting their
uploaded videos trending. Furthermore, we conduct a directional-relationship
analysis among all pairs of trending videos time-series that we have monitored.
We employ Granger Causality (GC) with significance testing to conduct this
analysis. Unlike traditional correlation measures, our directional-relationship
analysis provides a deeper insight onto the viewership pattern of different
categories of trending videos. Trending videos and their channels have clear
distinct statistical attributes when compared to other YouTube content that has
not been labeled as trending. Our results also reveal a highly asymmetric
directional-relationship among different categories of trending videos. Our
directionality analysis also shows a clear pattern of viewership toward popular
categories, whereas some categories tend to be isolated.
