Unknown

Dataset Information

Predictability of real temporal networks.


ABSTRACT: Links in most real networks often change over time. Such temporality of links encodes the ordering and causality of interactions between nodes and has a profound effect on network dynamics and function. Empirical evidence has shown that the temporal nature of links in many real-world networks is not random. Nonetheless, it is challenging to predict temporal link patterns while considering the entanglement between topological and temporal link patterns. Here, we propose an entropy-rate-based framework, based on combined topological-temporal regularities, for quantifying the predictability of any temporal network. We apply our framework on various model networks, demonstrating that it indeed captures the intrinsic topological-temporal regularities whereas previous methods considered only tem

SUBMITTER: Tang D 

PROVIDER: S-EPMC8288877 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature