Targeted spreader identification via lexicographic core decomposition
Arianna D’Ulizia, Alessia D’Andrea, Riccardo Denni · 2026
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Description
Arianna D'Ulizia, Alessia D'Andrea, and Riccardo Denni refine a way to rank the best spreaders in a network when some kinds of nodes matter more than others, in a 2026 study. Classic peeling methods strip a network layer by layer to find its core, yet they score every category alike. Their version peels with a priority order over categories, honoring a user's ranking of which groups count most.
The method raced seventy nine rival measures on seven real networks. It placed the true top spreader highest on five of the seven sets. Ties were its weak spot, since many nodes shared top ranks. Pairing the peel order with a simple degree count broke ties best, reliably lifting true spreaders into the top group. The code is shared freely for other teams to test.
Catalog record
| CREATOR | Arianna D’Ulizia, Alessia D’Andrea, Riccardo Denni |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 139657 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |