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To improve the quality of experience (QoE), especially under moderate to hightraffic demand, it is important to understand the impact of the network andapplication QoS on user experience. This paper comparatively evaluates theimpact of impairments, their intensity and temporal dynamics, on userengagement in the context of video streaming. The analysis employed two largeYouTube datasets. To characterize the user engagement and the impact ofimpairments, several new metrics were defined. We assessed whether or not thereis a statistically significant relationship between different types ofimpairments and QoE and user engagement metrics, taking into account not onlythe characteristics of the impairments but also the covariates of the session(e.g., video duration, mean datarate). After observing the relationships acrossthe entire dataset, we tested whether these relationships also persist underspecific conditions with respect to the covariates. The introduction of severalnew metrics and of various covariates in the analysis are two innovativeaspects of this work. We found that the number of negative bitrate changes(BR-) is a stronger predictor of abandonment than rebufferrings (RB). Evenpositive bitrate changes (BR+) are associated with increases in abandonment.Specifically, BR+ in low resolution sessions is not well received. Temporaldynamics of the impairments have also an impact: a BR- that follows much latera RB appears to be perceived as a worse impairment than a BR- that occursimmediately after a RB. These results can be used to guide the design of thevideo streaming adaptation as well as suggest which parameters should be variedin controlled field studies.

Should I stay or should I go: Analysis of the impact of application QoS on user engagement in YouTube