activity
20182026
most citedHypergraphx: a library for higher-order network analysis

40 citations · 48 across the 7 of their papers we have counts for

collaborators

12 papers

cs.SI2026

Motifs in temporal hypergraphs

Quintino Francesco Lotito, Lorenzo Betti, Federico Battiston +1

Network motifs, recurrent local patterns of interactions in graphs, provide fundamental insights on the interplay between structure and functionality in complex systems. Many real-…

physics.soc-ph20261 cited

Hypergraphx-data: a repository for higher-order network data

Quintino Francesco Lotito, Lorenzo Betti, Berné Nortier +2

The availability of network datasets advances research in network science, machine learning and related fields by enabling empirical analyses and their reproducibility, algorithm d…

physics.soc-ph20251 cited

HIF: The hypergraph interchange format for higher-order networks

Martín Coll, Cliff A. Joslyn, Nicholas W. Landry +5

Many empirical systems contain complex interactions of arbitrary size, representing, for example, chemical reactions, social groups, co-authorship relationships, and ecological dep…

physics.soc-ph2024

The microscale organization of directed hypergraphs

Quintino Francesco Lotito, Alberto Vendramini, Alberto Montresor +1

Many real-world complex systems are characterized by non-pairwise -- higher-order -- interactions among system's units, and can be effectively modeled as hypergraphs. Directed hype…

cs.SI2024

Influence Maximization in Hypergraphs using Multi-Objective Evolutionary Algorithms

Stefano Genetti, Eros Ribaga, Elia Cunegatti +2

The Influence Maximization (IM) problem is a well-known NP-hard combinatorial problem over graphs whose goal is to find the set of nodes in a network that spreads influence at most…

physics.soc-ph2024

Patterns in temporal networks with higher-order egocentric structures

Beatriz Arregui-García, Antonio Longa, Quintino Francesco Lotito +2

The analysis of complex and time-evolving interactions like social dynamics represents a current challenge for the science of complex systems. Temporal networks stand as a suitable…