Impact of Quality Factors on Users’ Viewing Behaviors in Adaptive Bitrate Streaming Services
Shoko Takahashi, Kazuhisa Yamagishi, Pierre R LeBreton, Jun Okamoto · 2019
Adaptive bitrate streaming services for mobile terminals have drastically spread in recent years, and it is becoming more important for service providers to increase users' satisfaction by understanding users' viewing behaviors (e.g., how long users watch videos, and why users quit viewing videos) and taking measures such as appropriately designing the quality levels of the videos to be placed on their distribution servers. To investigate the impacts of quality factors on users' viewing behaviors in adaptive bitrate streaming, we conducted an experiment in which participants could freely search and watch videos on smartphones under various network conditions. Through 800 10-minute tests, 1,449 valid views were collected, and the collected dataset was analyzed to characterize the impacts of the initial loading delay, average bitrate, and stalling events on the cumulative quit rate (CQR) of users. Furthermore, the impacts of the average bitrate and stalling events were evaluated quantitatively, using the 2-sample Anderson-Darling test, as well as the combined impact of these two quality factors. The characteristics of the impacts of the above quality factors indicate the possibility of applying survival analysis for our dataset, and suggest that the average bitrate, the number of stalling events, and the average stalling duration should be considered as the external covariates when building a model to estimate the users' viewing time.