Abstract
In recent years the study of networks has grown across the social, natural, and computer sciences. As numerous fields and disciplines have taken up formal network methodology, however, distinctions between human interactional and other types of networks have become blurred. This article argues for the utility of stepping back from the current state of affairs and asking “what exactly is social about social network analysis?” Answering this question requires drawing on current work in social cognition and cultural evolution to better account for the unique reflexive and adaptive nature of human experience and behavior within socio-cognitive niches. The study of diffusion and homophily are reexamined in light of this perspective on culture and cognition. The article concludes with a brief discussion of the broader implications of taking the human component of social networks more seriously.
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Notes
While graph theory is the dominant approach to formal network analysis, other methods, like multidimensional scaling, can also be employed (e.g., Barrett and Rice 1985).
Brandes et al. skeptically call this an effort to find a GrUNT, or Grand Unified Network Theory, in the premier issue of Network Science (2013).
In many ways the core issue in the comparative study of social cognition remains Darwin’s claim “that the difference in mind between man and the higher animals... is certainly one of degree and not of kind” (1974, p. 122). This question of whether human cognition is fundamentally different from animal cognition or only a variation of it is ultimately not fundamental for the argument of this paper, however. Whether other animals have, for example, rudimentary Theory of Mind capabilities does not change the fact that for many types of empirical problems analysts studying human social networks should take higher order social cognition into account.
The social intelligence hypothesis is also referred to as the Machiavellian hypothesis (Byrne and Whiten 1988). The cultural intelligence hypothesis can be seen as a special case of the social intelligence hypothesis that focuses especially on the transmission of culture. Another complementary, and specifically human focused, perspective is the Vygotskian intelligence hypothesis that emphasizes the central role of social cooperation in human evolution (Moll and Tomasello 2007).
One of the significant pieces of evidence for the social intelligence hypothesis is the strong correlation between increase in neocortex and group size, something true not only for primates, but for mammals more generally (Dunbar 1992). Moreover, the human neocortex is larger in other primates in exactly these areas that support social competencies that seem to be unique to humans like Theory of Mind and sense of self (Flinn et al. 2005).
As will be discussed later, the ability to reason about higher-order relationships is facilitated by language and the ability to name relationships (Penn et al. 2008).
Another way to think about the distinction between physical and socio-cognitive niches is Hacking’s notion of “transient” and “permanent” kinds (1999: chapter 4). As Machery and Faucher write, “[a] kind is transient if its reality depends on a cultural niche, that is, on the ideas and social practices that are prevalent in a given society at a given time. The dependence is such that were the niche of a transient kind to disappear, the kind would disappear as well…By contrast, the reality of permanent kinds basically natural kinds…is not dependent on any culture, even if the concepts that refer to them may vary across cultures (2005, pp. 1013–1014).” For a similar argument, see Searle (1995).
As Mesoudi notes, there is a double-disassociation between behavior and ecology in that “two societies living the same environment can have totally different behavioral practices, conversely two societies with similar behavioral practices may live very different environments (2011, pp. 12–13).” Moreover, similar stimuli and activities can lead to different brain responses depending on a person’s cultural and social background (Roepstoroff et al. 2010). The relationship between brain and world is complex and culturally mediated.
See Hacking (2004) for discussion of the difference between discourse in the abstract and in face-to-face interaction.
We may of course also be interested in a fuller account of disease spread that includes understanding why the actor engaged in the practice that led to transmission, but that is a separate issue.
All of these categories refer to different types of 'social learning biases’, the innate or learned rules people use when copying others.
A key issue in the research literature is differentiating social learning from either individual learning (learning with no influence from conspecifics) or genetic inheritance (acquisition of information via genetic inheritance). Teasing these apart empirically is a difficult process.
This process seems to work in two directions. Through diffusion, we unintentionally change information to make it easier to remember and learn (Kirby et al. 2008). We also take advantage of this process and purposefully shape information to make it ‘stickier.’
One example of a TRIM from the network literature given by Mesoudi (2011, p. 68) is Roger’s study of health workers’ attempts to convince housewives in Puruvian villages to boil water to reduce spread of waterborne disease. The effort failed because it was inconsistent with existing folk beliefs about food and illness.
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Diehl, D.K. What exactly is “social” about social networks?: Accounting for socio-cultural context in networks of human interaction. Qual Quant 57, 1369–1392 (2023). https://doi.org/10.1007/s11135-022-01410-z
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DOI: https://doi.org/10.1007/s11135-022-01410-z