  The significance of the PageRank algorithm in shaping the modern Internet
cannot be overstated, and its Complex Network theory foundations continue to be
a subject of research. In this article we carry out a systematic study of the
structural and parametric controllability of PageRank's outcomes, translating a
spectral Graph Theory problem into a geometric one, where a natural
characterization of its rankings emerges. Furthermore, we show that the change
of perspective employed can be applied to the biplex PageRank proposal,
performing numerical computations on both real and synthetic network datasets
to compare centrality measures used.
