Method evidence record
Temporal Eigenvector Centrality
Temporal eigenvector centrality extends the classical eigenvector centrality to networks that change over time. By accounting for the ordering and timing of connections, it identifies nodes that are influential not merely because of many simultaneous connections, but because they sit at the crossroads of sequentially important pathways across multiple time slices of the network.
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Temporal Eigenvector Centrality (Dynamic Eigenvector-Based Node Importance in Time-Varying Networks)
Taxonomic method record · ml-model / network-analysis
- Grindrod, P., Parsons, M. C., Higham, D. J., & Estrada, E. (2011). Communicability across evolving networks. Physical Review E, 83(4), 046120. · DOI 10.1103/PhysRevE.83.046120
- Taylor, D., Myers, S. A., Clauset, A., Porter, M. A., & Mucha, P. J. (2017). Eigenvector-based centrality measures for temporal networks. Multiscale Modeling and Simulation, 15(1), 537-574. · DOI 10.1137/16M1066142
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