  To improve the quality of experience (QoE), especially under moderate to high
traffic demand, it is important to understand the impact of the network and
application QoS on user experience. This paper comparatively evaluates the
impact of impairments, their intensity and temporal dynamics, on user
engagement in the context of video streaming. The analysis employed two large
YouTube datasets. To characterize the user engagement and the impact of
impairments, several new metrics were defined. We assessed whether or not there
is a statistically significant relationship between different types of
impairments and QoE and user engagement metrics, taking into account not only
the characteristics of the impairments but also the covariates of the session
(e.g., video duration, mean datarate). After observing the relationships across
the entire dataset, we tested whether these relationships also persist under
specific conditions with respect to the covariates. The introduction of several
new metrics and of various covariates in the analysis are two innovative
aspects of this work. We found that the number of negative bitrate changes
(BR-) is a stronger predictor of abandonment than rebufferrings (RB). Even
positive bitrate changes (BR+) are associated with increases in abandonment.
Specifically, BR+ in low resolution sessions is not well received. Temporal
dynamics of the impairments have also an impact: a BR- that follows much later
a RB appears to be perceived as a worse impairment than a BR- that occurs
immediately after a RB. These results can be used to guide the design of the
video streaming adaptation as well as suggest which parameters should be varied
in controlled field studies.
