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In a temporal network causal paths are characterized by the fact that linksfrom a source to a target must respect the chronological order. In this articlewe study the causal paths structure in temporal networks of human face to faceinteractions in different social contexts. In a static network paths aretransitive i.e. the existence of a link from $a$ to $b$ and from $b$ to $c$implies the existence of a path from $a$ to $c$ via $b$. In a temporal networkthe chronological constraint introduces time correlations that affectstransitivity. A probabilistic model based on higher order Markov chains showsthat correlations that can invalidate transitivity are present only when thetime gap between consecutive events is larger than the average value and arenegligible below such a value. The comparison between the densities of thetemporal and static accessibility matrices shows that the static representationcan be used with good approximation. Moreover, we quantify the extent of thecausally connected region of the networks over time.

Causal Paths in Temporal Networks of Face-to-Face Human Interactions