  The labeling of point features on a map is a well-studied topic. In a static
setting, the goal is to find a non-overlapping label placement for (a subset
of) point features. In a dynamic setting, the set of point features and their
corresponding labels change, and the labeling has to adapt to such changes. To
aid the user in tracking these changes, we can use morphs, here called
transitions, to indicate how a labeling changes. Such transitions have not
gained much attention yet, and we investigate different types of transitions
for labelings of points, most notably consecutive transitions and simultaneous
transitions. We give (tight) bounds on the number of overlaps that can occur
during these transitions. When each label has a (non-negative) weight
associated to it, and each overlap imposes a penalty proportional to the weight
of the overlapping labels, we show that it is NP-complete to decide whether the
penalty during a simultaneous transition has weight at most $k$. Finally, in a
case study, we consider geotagged Twitter data on a map, by labeling points
with rectangular labels showing tweets. We developed a prototype implementation
to evaluate different transition styles in practice, measuring both number of
overlaps and transition duration.
