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 Lévy 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.
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