Intelligence of small groups
Giovanni Francesco Massari, Garland Culbreth, Roberto Failla, Mauro, Bologna, Bruce J. West, Paolo Grigolini

TL;DR
This paper models social group dynamics as a self-organizing critical system, showing that group size of 150 optimizes information transmission efficiency, aligning with Dunbar's number.
Contribution
It introduces a criticality-based model explaining why 150 is optimal for social cohesion and information flow, linking it to phase transition phenomena.
Findings
Maximum information transmission at N=150
Criticality induces power-law event distributions
Group decision persistence aligns with KPZ scaling at N=150
Abstract
Dunbar hypothesized that is the maximal number of people with whom one can maintain stable social relationships. We explain this effect as being a consequence of a process of self-organization between units leading their social system to the edge of phase transition, usually termed criticality. Criticality generates events, with an inter-event time interval distribution characterized by an inverse power law (IPL) index . These events break ergodicity and we refer to them as crucial events. The group makes decisions and the time persistence of each decision is given by another IPL distribution with IPL index , which is different from if . We prove that when the number of interacting individuals is equal to , these two different IPL indexes become identical, with the effect of generating the Kardar Parisi Zhang (KPZ) scaling $\delta…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComplex Network Analysis Techniques · Complex Systems and Time Series Analysis · Opinion Dynamics and Social Influence
