  Modeling visual saliency in graphical user interfaces (GUIs) allows to
understand how people perceive GUI designs and what elements attract their
attention. One aspect that is often overlooked is the fact that computational
models depend on a series of design parameters that are not straightforward to
decide. We systematically analyze how different design parameters affect
scanpath evaluation metrics using a state-of-the-art computational model
(DeepGaze++). We particularly focus on three design parameters: input image
size, inhibition-of-return decay, and masking radius. We show that even small
variations of these design parameters have a noticeable impact on standard
evaluation metrics such as DTW or Eyenalysis. These effects also occur in other
scanpath models, such as UMSS and ScanGAN, and in other datasets such as
MASSVIS. Taken together, our results put forward the impact of design decisions
for predicting users' viewing behavior on GUIs.
