Intelligence of small groups

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 $150$ 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 $N$ 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 $\mu_{S}<2$. 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 $\mu_{R}$, which is different from $\mu_{S}$ if $N\neq 150$. We prove that when the number of interacting individuals is equal to $150$, these two different IPL indexes become identical, with the effect of generating the Kardar Parisi Zhang (KPZ) scaling $\delta =1/3$. We argue this to be an enhanced form of intelligence, which generates efficient information transmission within the group. We prove the inflrmation transmission efficiency is maximal when $N=150$, the Dunbar number.