Collective memory, consensus, and learning explained by social cohesion

TL;DR

This paper explains how social cohesion, network structure, and algebraic connectivity influence collective memory, consensus, and learning in human groups, providing a mathematical basis for understanding social dynamics.

Contribution

It introduces the algebraic connectivity of social networks as a key factor in explaining and predicting collective social behaviors and norms.

Findings

Higher algebraic connectivity correlates with stronger social cohesion.

Network proximity and redundancy influence collective learning and norm formation.

Algebraic connectivity predicts group synchronization and bonding outcomes.

Abstract

Humans cluster in social groups where they discuss their shared past, problems, and potential solutions; they learn collectively when they repeat activities; they establish social norms; they synchronize when they sing or dance together; and they bond through social cohesion. A group is more cohesive if its members are closer together in their network and are bonded by multiple connections. Network proximity and redundancy are indicated by the second smallest eigenvalue of the Laplacian matrix of the group network, called the algebraic connectivity. This eigenvalue is key to explaining and predicting the outcomes of said activities.