  Dynamics of complex social systems has often been described in the framework
of temporal networks, where links are considered to exist only at the moment of
interaction between nodes. Such interaction patterns are not only driven by
internal interaction mechanisms, but also affected by environmental changes. To
investigate the impact of the environmental changes on the dynamics of temporal
networks, we analyze several face-to-face interaction datasets using the
multiscale entropy (MSE) method to find that the observed temporal correlations
can be categorized according to the environmental similarity of datasets such
as classes and break times in schools. By devising and studying a temporal
network model considering a periodically changing environment as well as a
preferential activation mechanism, we numerically show that our model could
successfully reproduce various empirical results by the MSE method in terms of
multiscale temporal correlations. Our results demonstrate that the
environmental changes can play an important role in shaping the dynamics of
temporal networks when the interactions between nodes are influenced by the
environment of the systems.
