Dynamical Structure of a Traditional Amazonian Social Network.

Paul Hooper,Simon DeDeo,Hillard Kaplan,Ann Caldwell Hooper,Michael Gurven

doi:10.3390/e15114932

Abstract

Reciprocity is a vital feature of social networks, but relatively little is known about its temporal structure or the mechanisms underlying its persistence in real world behavior. In pursuit of these two questions, we study the stationary and dynamical signals of reciprocity in a network of manioc beer (Spanish: chicha; Tsimane’: shocdye’) drinking events in a Tsimane’ village in lowland Bolivia. At the stationary level, our analysis reveals that social exchange within the community is heterogeneously patterned according to kinship and spatial proximity. A positive relationship between the frequencies at which two families host each other, controlling for kinship and proximity, provides evidence for stationary reciprocity. Our analysis of the dynamical structure of this network presents a novel method for the study of conditional, or non-stationary, reciprocity effects. We find evidence that short-timescale reciprocity (within three days) is present among non- and distant-kin pairs; conversely, we find that levels of cooperation among close kin can be accounted for on the stationary hypothesis alone.

Highlights

The evolutionary social and life sciences seek to understand both the ultimate evolutionary logic that motivates the formation of valuable social relationships, as well as the proximate mechanisms that support the stability of these relationships over time [2,3,4]
We summarize a number of characteristics of the network and report our results for kinship and stationary and dynamical reciprocity
We have presented new results on the nature of cooperation and the maintenance of social ties and have introduced new methods to detect signals of dynamical processes within social networks

Summary

Introduction

The evolutionary social and life sciences seek to understand both the ultimate evolutionary logic that motivates the formation of valuable social relationships, as well as the proximate mechanisms that support the stability of these relationships over time [2,3,4]. Longitudinal social network data provide an arena for evaluating the predictions of evolutionary models for relationship formation and maintenance through time. These data inform us of the time dimension of network activity, a topic of both empirical and theoretical interest in the network sciences [5,6]. These data can shed light on the time scale of the processes that are in motion within social and biological systems [7,8,9]. In addition to the food value of the beer, conviviality and intoxication create a social venue for conversation, exchange and friendship

Methods

Discussion

Conclusion