  The study of self-propelled particles is a fast-growing research topic where
biologically inspired movement is increasingly becoming of much interest. A
relevant example is the collective motion of social insects, whose variety and
complexity offer fertile grounds for theoretical abstractions. It has been
demonstrated that the collective motion involved in the searching behavior of
termites is consistent with self-similarity, anomalous diffusion and L\'evy
walks. In this work, we use visibility graphs -- a method that maps time series
into graphs and quantifies the signal complexity via graph topological metrics
-- in the context of social insects foraging trajectories extracted from
experiments. Our analysis indicates that the patterns observed for isolated
termites change qualitatively when the termite density is increased, and such
change cannot be explained by jamming effects only, pointing to collective
effects emerging due to non-trivial foraging interactions between insects as
the cause. Moreover, we find that such an onset of complexity is maximized for
intermediate termite densities.
