Predicting User Quitting Ratio in Adaptive Bitrate Video Streaming

To improve user engagement such as viewing time, this paper addresses the understanding and prediction of the
user quitting ratio
for users watching videos using adaptive bit rate video streaming. The
user quitting ratio
is defined as the percentage of users still watching videos at a given time. To perform this study, five subjective experiments involving up to 264 participants were conducted in a laboratory setting. Results indicated the effects of coding quality, initial buffering, and midway stalling on
user quitting ratio
. Then, a framework was defined to predict the
user quitting ratio
as a function of time. This framework achieves good prediction accuracy and can be used in multiple scenarios including when quality adaptation and stalling occur. Finally, it is suitable for monitoring applications where bitstream are encrypted and low processing cost is required.