Predicting User Quitting Ratio in Adaptive Bitrate Video Streaming
Pierre R LeBreton, Kazuhisa Yamagishi · IEEE Transactions on Multimedia · 2020
To improve user engagement such as viewing time, this paper addresses the understanding and prediction of theuser quitting ratiofor users watching videos using adaptive bit rate video streaming. Theuser quitting ratiois 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 onuser quitting ratio. Then, a framework was defined to predict theuser quitting ratioas 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.