  We explore how the definition of a void influences the conclusions drawn
about the impact of the void environment on galactic properties using two
void-finding algorithms in the Void Analysis Software Toolkit: V2, a Python
implementation of ZOBOV, and VoidFinder, an algorithm which grows and merges
spherical void regions. Using the Sloan Digital Sky Survey Data Release 7, we
find that galaxies found in VoidFinder voids tend to be bluer, fainter, and
have higher (specific) star formation rates than galaxies in denser regions.
Conversely, galaxies found in V2 voids show no significant differences when
compared to galaxies in denser regions, inconsistent with the large-scale
environmental effects on galaxy properties expected from both simulations and
previous observations. These results align with previous simulation results
that show V2-identified voids "leaking" into the dense walls between voids
because their boundaries extend up to the density maxima in the walls. As a
result, when using ZOBOV-based void finders, galaxies likely to be part of wall
regions are instead classified as void galaxies, a misclassification that can
be critical to our understanding of galaxy evolution.
