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Review
. 2020 Aug;476(2240):20200446.
doi: 10.1098/rspa.2020.0446. Epub 2020 Aug 26.

Structure and function in human and primate social networks: implications for diffusion, network stability and health

R I M Dunbar  1
Affiliations
Review

Structure and function in human and primate social networks: implications for diffusion, network stability and health

R I M Dunbar. Proc Math Phys Eng Sci. 2020 Aug.

Abstract

The human social world is orders of magnitude smaller than our highly urbanized world might lead us to suppose. In addition, human social networks have a very distinct fractal structure similar to that observed in other primates. In part, this reflects a cognitive constraint, and in part a time constraint, on the capacity for interaction. Structured networks of this kind have a significant effect on the rates of transmission of both disease and information. Because the cognitive mechanism underpinning network structure is based on trust, internal and external threats that undermine trust or constrain interaction inevitably result in the fragmentation and restructuring of networks. In contexts where network sizes are smaller, this is likely to have significant impacts on psychological and physical health risks.

Keywords: fractal network structure; morbidity; mortality; network fragmentation; time constraint; trust.

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Conflict of interest statement

I declare I have no competing interests.

Figures

Figure 1.
Figure 1.
(a) Layers within a large European cellphone dataset, based on frequency of calling. Layers identified by Jenks clustering algorithm. Reproduced from [19]. (b) Optimal number of clusters identified by k-means clustering algorithm in three online datasets. Reproduced from [68].
Figure 2.
Figure 2.
Structure of human egocentric social networks. The number of people included in each circle increases, but the frequency of contact and emotional closeness declines, with each layer. Redrawn from [19]. The outermost layer (5000) was identified by experimental studies of face recognition (the number of faces that can be recognized as known by sight) [80]. (Online version in colour.)
Figure 3.
Figure 3.
Frequency per day with which people contacted individual members of each layer in their social network. Sample: complete social networks of 251 UK and Belgian women. Reproduced from [17].
Figure 4.
Figure 4.
Cumulative proportional composition across layers of egocentric networks predicted by a one-dimensional Bayesian decision model. When the Lagrange multiplier µ < 0, the network structure reverses from the conventional structure (upper curve) to a reversed structure (lower curve). Reproduced from [128]. (Online version in colour.)
Figure 5.
Figure 5.
(a) Cumulative probability of hearing about an item of information through face-to-face contact with an individual who has that knowledge in communities of different size (5, 15, 50, 150, 500, 1500 and 5000), based on the contact rates shown in figure 3 extrapolated out to higher layers. The model assumes that 1% of all community members are initially seeded with the information. The cumulative probability asymptotes at a network size of approximately 150, but the optimum number of alters is 50 (identified by the point at which the curve begins to decelerate, defined by e−1 of the way down from the asymptote) since after this, the benefits of increasing network size diminish exponentially. Reproduced from [130]. (b) Effect on reachability of removing nodes in different layers of egocentric twitter graphs: the larger the effect, the greater the disruption on information flow. The horizontal dotted lines demarcate 1/eth from the asymptote, and the vertical dotted line the optimal group size for information diffusion. Data from [133].
Figure 6.
Figure 6.
Change in the mean emotional closeness (on a 1–10 linear scale) to all members of the extended family (kin) and the original set of friends at time 0 after Ego moves to another city and cannot meet up with them so easily. Family relationships are extremely robust to not being contacted, but friendships decline in emotional closeness very quickly if they are not continuously reinforced. Redrawn from [141].
See this image and copyright information in PMC

References

    1. Clayton JB, et al. 2018. The gut microbiome of nonhuman primates: lessons in ecology and evolution. Am. J. Primatol. 80, e22867 ( 10.1002/ajp.22867) - DOI - PubMed
    1. Münger E, Montiel-Castro AJ, Langhans W, Pacheco-López G. 2018. Reciprocal interactions between gut microbiota and host social behavior. Front. Integr. Neurosci. 12, 21 ( 10.3389/fnint.2018.00021) - DOI - PMC - PubMed
    1. Sarkar A, et al. In press The role of the microbiome in the biology of social behaviour. Biol. Rev.
    1. Anderson RM, May RM. 1991. Infectious diseases of humans: dynamics and control. Oxford, UK: Oxford University Press.
    1. Boyd R, Richerson PJ. 1985. Culture and the evolutionary process. Chicago, IL: University of Chicago Press.

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