  Investigating the frequency and distribution of small subgraphs with a few
nodes/edges, i.e., motifs, is an effective analysis method for static networks.
Motif-driven analysis is also useful for temporal networks where the spectrum
of motifs is significantly larger due to the additional temporal information on
edges. This variety makes it challenging to design a temporal motif model that
can consider all aspects of temporality. In the literature, previous works have
introduced various models that handle different characteristics. In this work,
we compare the existing temporal motif models and evaluate the facets of
temporal networks that are overlooked in the literature. We first survey four
temporal motif models and highlight their differences. Then, we evaluate the
advantages and limitations of these models with respect to the temporal
inducedness and timing constraints. In addition, we suggest a new lens, event
pairs, to investigate temporal correlations. We believe that our comparative
survey and extensive evaluation will catalyze the research on temporal network
motif models.
