Relating size and functionality in human social networks through complexity.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 32690712.
- Also identified by DOI 10.1073/pnas.2006875117 and PMC identifier 7414177.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Extensive empirical evidence suggests that there is a maximal number of people with whom an individual can maintain stable social relationships (the Dunbar number). We argue that this arises as a consequence of a natural phase transition in the dynamic self-organization among <i>N</i> individuals within a social system. We present the calculated size dependence of the scaling properties of complex social network models to argue that this collective behavior is an enhanced form of collective intelligence. Direct calculation establishes that the complexity of social networks as measured by their scaling behavior is nonmonotonic, peaking around 150, thereby providing a theoretical basis for the value of the Dunbar number. Thus, we establish a theory-based bridge spanning the gap between sociology and psychology.
Medical subject headings
- Models, Theoretical
- Social Behavior
- Social Networking