Collective Decision-Making on Triadic Graphs

Ilja Rausch*, Yara Khaluf, Pieter Simoens

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

7 Citations (Scopus)

Abstract

Many real-world networks exhibit community structures and non-trivial clustering associated with the occurrence of a considerable number of triangular subgraphs known as triadic motifs. Triads are a set of distinct triangles that do not share an edge with any other triangle in the network. Network motifs are subgraphs that occur significantly more often compared to random topologies. Two prominent examples, the feedforward loop and the feedback loop, occur in various real-world networks such as gene-regulatory networks, food webs or neuronal networks. However, as triangular connections are also prevalent in communication topologies of complex collective systems, it is worthwhile investigating the influence of triadic motifs on the collective decision-making dynamics. To this end, we generate networks called Triadic Graphs (TGs) exclusively from distinct triadic motifs. We then apply TGs as underlying topologies of systems with collective dynamics inspired from locust marching bands. We demonstrate that the motif type constituting the networks can have a paramount influence on group decision-making that cannot be explained solely in terms of the degree distribution. We find that, in contrast to the feedback loop, when the feedforward loop is the dominant subgraph, the resulting network is hierarchical and inhibits coherent behavior.

Original languageEnglish
Title of host publicationComplex Networks XI - Proceedings of the 11th Conference on Complex Networks, CompleNet 2020
EditorsHugo Barbosa, Ronaldo Menezes, Jesus Gomez-Gardenes, Bruno Gonçalves, Giuseppe Mangioni, Marcos Oliveira
PublisherSpringer
Pages119-130
Number of pages12
ISBN (Print)9783030409425
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event11th International Conference on Complex Networks, CompleNet 2020 - Exeter, United Kingdom
Duration: 31 Mar 20203 Apr 2020

Publication series

NameSpringer Proceedings in Complexity
ISSN (Print)2213-8684
ISSN (Electronic)2213-8692

Conference

Conference11th International Conference on Complex Networks, CompleNet 2020
Country/TerritoryUnited Kingdom
CityExeter
Period31/03/203/04/20

Keywords

  • Collective decision-making
  • Complex networks
  • Feedforward loop
  • Group coherence
  • Hierarchality
  • Triadic motifs

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