output
20172023
most citedDynamics on higher-order networks: A review

551 citations

Showing 2022Show all

8 papers · 1 filter

q-bio.PE2022★ 7 cited

Oppressed species can form a winning pair in a multi-species ecosystem

Attila Szolnoki, Matjaz Perc

The self-protection of alliances against external invaders is a key concept behind the maintenance of biodiversity in the face of natural selection. But since these alliances, whic…

physics.soc-ph2022★ 29 cited

Why are there six degrees of separation in a social network?

Ivan Samoylenko, David Aleja, Eva Primo +11

A wealth of evidence shows that real world networks are endowed with the small-world property i.e., that the maximal distance between any two of their nodes scales logarithmically…

physics.soc-ph2022★ 41 cited

Machine Learning Partners in Criminal Networks

Diego D. Lopes, Bruno R. da Cunha, Alvaro F. Martins +5

Recent research has shown that criminal networks have complex organizational structures, but whether this can be used to predict static and dynamic properties of criminal networks…

physics.data-an2022★ 7 cited

Clustering free-falling paper motion with complexity and entropy

Arthur A. B. Pessa, Matjaz Perc, Haroldo V. Ribeiro

Many simple natural phenomena are characterized by complex motion that appears random at first glance, but that often displays underlying patterns and behavior that can be clustere…

physics.soc-ph2022★ 1 cited

Universality of political corruption networks

Alvaro F. Martins, Bruno R. da Cunha, Quentin S. Hanley +3

Corruption crimes demand highly coordinated actions among criminal agents to succeed. But research dedicated to corruption networks is still in its infancy and indeed little is kno…

physics.soc-ph2022★ 551 cited

Dynamics on higher-order networks: A review

Soumen Majhi, Matjaz Perc, Dibakar Ghosh

Network science has evolved into an indispensable platform for studying complex systems. But recent research has identified limits of classical networks, where links connect pairs…

physics.data-an2022★ 41 cited

Determining liquid crystal properties with ordinal networks and machine learning

Arthur A. B. Pessa, Rafael S. Zola, Matjaz Perc +1

Machine learning methods are becoming increasingly important for the development of materials science. In spite of this, the use of image analysis in the development of these syste…

nlin.CD2022★ 79 cited

Swarmalators under competitive time-varying phase interactions

Gourab K. Sar, Sayantan Nag Chowdhury, Matjaz Perc +1

Swarmalators are entities with the simultaneous presence of swarming and synchronization that reveal emergent collective behavior due to the fascinating bidirectional interplay bet…