Detecting Dynamic States of Temporal Networks Using Connection Series Tensors

@article{Cao2020DetectingDS,
  title={Detecting Dynamic States of Temporal Networks Using Connection Series Tensors},
  author={Shun Cao and Hiroki Sayama},
  journal={ArXiv},
  year={2020},
  volume={abs/2007.12756}
}
Many temporal networks exhibit multiple system states, such as weekday and weekend patterns in social contact networks. The detection of such distinct states in temporal network data has recently been studied as it helps reveal underlying dynamical processes. A commonly used method is network aggregation over a time window, which aggregates a subsequence of multiple network snapshots into one static network. This method, however, necessarily discards temporal dynamics within the time window… Expand

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