Temporal Network Motifs: Models, Limitations, Evaluation

@article{Liu2021TemporalNM,
  title={Temporal Network Motifs: Models, Limitations, Evaluation},
  author={Penghang Liu and Valerio Guarrasi and Ahmet Erdem Sariy{\"u}ce},
  journal={ArXiv},
  year={2021},
  volume={abs/2005.11817}
}
Investigating the frequency and distribution of small subgraphs with a few nodes/edges, i.e., motifs, is an effective analysis method for static networks. Motif-driven analysis is also useful for temporal networks where the number of motifs is significantly larger due to the additional temporal information on edges. This variety makes it challenging to design a temporal motif model that can consider all aspects of temporality. In the literature, previous works have introduced various models… 
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