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

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.


Recommendation?
Accept with minor revision (please list in comments)

Comments to the Author(s)
This manuscript provides an interesting review and commentary of the psychological and behavioural determinants of social network structure in humans and primates. The manuscript is of the form of a review/synthesis of previous research, rather than presenting any novel findings.
Section 2 overviews the common structure of human and primate networks, and the behavioural and psychological determinants of this structure.
Section 3 overviews that human social networks are layered, and that this layered structure is consistent across different media, and that this also applies to primate networks. It also considers some of the determinants of heterogeneity in human social networks -including sex, age, and the distinction between family and friend ties.
Section 4 explains the bonding process in primates. It documents the role of grooming, and the ways that humans have managed to expand their number of contacts they 'groom' by undertaking other activities that trigger the same endorphin system. It also explains the cognitive mechanism underlying bonding in primates -being able to predict and rely upon another's behaviour, and how this leads to homophily in social networks.
Section 5 overviews the way in which time constraints determine the structure of social networks. It surveys different models that aim to recreate the structure of human social networks.
Section 6 surveys how this structure affects the diffusion of e.g. information.
Section 7 looks at some of the social implications of this social network structure.

Specific comments:
The 'fractal structure of networks' needs to be defined more clearly/rigorously. "They also treat diseases and innovations as bipolar phase states (you either have them or you don't)." -True, but this isn't an issue addressed anyway this manuscript, it would be good to hear the author's thoughts on this.
"Although network analysts began to appreciate quite early on that human populations are highly structured and that this structure could dramatically affect how innovations propagate through networks (6,7) Watts & Stogatz 1998; Keeling 1999), only very recently has it been appreciated that the structure created by social or spatial organisation might affect the speed with which diseases or information propagate through a population (8-10) Read et al. 2008;Danon et al. 2013;Read et al. 2014)." -I don't think I understand the difference between these two situations & both of the early papers focus on disease spread (On the distinction between family and friends). "Although almost never considered in models of network dynamics, this division can have significant consequences for the dynamics of networks, especially between countries characterised by small and large families." Household models are epidemiological models built with this consideration in mind -the distinction between withinhousehold interactions and between-household interactions. There is a wealth of literature on such models (see e.g. House andKeeling (2009), Pellis Ferguson andFraser (2009)). In addition, many of the large simulation models combine households with social networks.
"A comparison of migrant versus host communities in Spain revealed that there is indeed a phase transition between conventionally structured networks (layers with a concave structure) to reversed networks (convex structures) at µ=0 (110) Tamarit et al. (104)." The concepts of convex and concave structure need to be defined and explained in more detail for the benefit of the reader.
"Much of the focus in network dynamics has been on disease propagation. In all these studies, networks are assumed to remain essentially static in structure over time." Many epidemic network models also consider dynamic network structures, (see e.g. Masuda and Holme (2017) for an overview of some recent methods).

Review form: Referee 2
Is the manuscript an original and important contribution to its field? Good

Is the paper of sufficient general interest? Excellent
Is the overall quality of the paper suitable? Good

Recommendation?
Accept with minor revision (please list in comments)

12-Jun-2020
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Yours sincerely Raminder Shergill proceedingsa@royalsociety.org Reviewer(s)' Comments to Author: Referee: 1 Comments to the Author(s) This manuscript provides an interesting review and commentary of the psychological and behavioural determinants of social network structure in humans and primates. The manuscript is of the form of a review/synthesis of previous research, rather than presenting any novel findings.
Section 2 overviews the common structure of human and primate networks, and the behavioural and psychological determinants of this structure.
Section 3 overviews that human social networks are layered, and that this layered structure is consistent across different media, and that this also applies to primate networks. It also considers some of the determinants of heterogeneity in human social networks -including sex, age, and the distinction between family and friend ties.
Section 4 explains the bonding process in primates. It documents the role of grooming, and the ways that humans have managed to expand their number of contacts they 'groom' by undertaking other activities that trigger the same endorphin system. It also explains the cognitive mechanism underlying bonding in primates -being able to predict and rely upon another's behaviour, and how this leads to homophily in social networks.
Section 5 overviews the way in which time constraints determine the structure of social networks. It surveys different models that aim to recreate the structure of human social networks.
Section 6 surveys how this structure affects the diffusion of e.g. information.
Section 7 looks at some of the social implications of this social network structure.
Specific comments: The 'fractal structure of networks' needs to be defined more clearly/rigorously. "They also treat diseases and innovations as bipolar phase states (you either have them or you don't)." -True, but this isn't an issue addressed anyway this manuscript, it would be good to hear the author's thoughts on this.
"Although network analysts began to appreciate quite early on that human populations are highly structured and that this structure could dramatically affect how innovations propagate through networks (6,7) Watts &amp; Stogatz 1998; Keeling 1999), only very recently has it been appreciated that the structure created by social or spatial organisation might affect the speed with which diseases or information propagate through a population (8-10) Read et al. 2008;Danon et al. 2013;Read et al. 2014)." -I don't think I understand the difference between these two situations &amp; both of the early papers focus on disease spread (On the distinction between family and friends). "Although almost never considered in models of network dynamics, this division can have significant consequences for the dynamics of networks, especially between countries characterised by small and large families." Household models are epidemiological models built with this consideration in mind -the distinction between withinhousehold interactions and between-household interactions. There is a wealth of literature on such models (see e.g. House andKeeling (2009), Pellis Ferguson andFraser (2009)). In addition, many of the large simulation models combine households with social networks.
"A comparison of migrant versus host communities in Spain revealed that there is indeed a phase transition between conventionally structured networks (layers with a concave structure) to reversed networks (convex structures) at µ=0 (110) Tamarit et al. (104)." The concepts of convex and concave structure need to be defined and explained in more detail for the benefit of the reader.
"Much of the focus in network dynamics has been on disease propagation. In all these studies, networks are assumed to remain essentially static in structure over time." Many epidemic network models also consider dynamic network structures, (see e.g. Masuda and Holme (2017) for an overview of some recent methods). On behalf of the Editor, I am pleased to inform you that your manuscript entitled "Structure and Function in Human and Primate Social Networks: Implications for Diffusion, Network Stability and Health" has been accepted in its final form for publication in Proceedings A.
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REVIEWER 1
This paper argues that human social networks are both more structured and smaller than is apparent from casual observation. The paper also notes that structure and size matter for disease and information transmission. An excellent survey of the literature on the size of social networks and the consistency of conclusions about network structure and size is provided. For the type of networks considered in this paper the points about structure and size are well supported. The argument that human social networks are not the simple networks analyzed in most of the simple models of disease transmission (such as branching processes) is compelling. It might be valuable to point out that those simple models are the basis for the critical R0 value that is so commonly used in public discussions of epidemics. Comment added to Introduction.
But it's also useful to note that models of disease transmission such as SIR, SIS and SIRS models can be applied to any network. The discussion in this paper is primarily focused on friendship networks (using a broad definition of friendship). For contagion of ideas, customs, fashion and the like this seems an appropriate definition of the relevant network upon which to study contagion. It's less clear that it leads to the appropriate definition of the network in which to study disease contagion. This surely depends on the disease, but for one which can apparently spread from person to person based on proximity, it doesn't seem appropriate. Casual contacts in a store or on a subway can spread the disease while friendships which don't currently involve physical interaction can't spread the disease. This was actually pointed out, but I have emphasised it. • It would be useful to comment on the relation between the structure of networks considered here and the observations about the importance of 1 long range ties as in Strogatz and Watts (Nature 1998) and Kleinberg (Nature 2000). I have added a comment on this very relevant point.

REVIEWER 2
This manuscript provides an interesting review and commentary of the psychological and behavioural determinants of social network structure in humans and primates. The manuscript is of the form of a review/synthesis of previous research, rather than presenting any novel findings.
Section 2 overviews the common structure of human and primate networks, and the behavioural and psychological determinants of this structure.