Dynamic social networks and reciprocity: comparing agent-based models and behavioural studies

21^st April 2015, 13:00 Ashton Lecture Theater
Dr Steve Phelps
Centre for Computational Finance and Economic Agents
University of Essex

Abstract

Many models of social network formation implicitly assume that network
properties are static in steady-state. In contrast, actual social networks are
highly dynamic: allegiances and collaborations expire and may or may not be
renewed at a later date. Moreover, empirical studies show that human social
networks are dynamic at the individual level but static at the global level:
individuals' degree rankings change considerably over time, whereas network
level metrics such as network diameter and clustering coefficient are relatively
stable. There have been some attempts to explain these properties of empirical
social networks using agent-based models in which agents play social dilemma
games with their immediate neighbours, but can also manipulate their network
connections to strategic advantage. However, such models cannot
straightforwardly account for reciprocal behaviour based on reputation scores
("indirect reciprocity"), which is known to play an important role in many
economic interactions. In order to account for indirect reciprocity, we model
the network in a bottom-up fashion: the network emerges from the low-level
interactions between agents. By so doing we are able to simultaneously account
for the effect of both direct reciprocity (e.g. "tit-for-tat") as well as
indirect reciprocity (helping strangers in order to increase one's reputation).
We test the implications of our model against a longitudinal dataset of
Chimpanzee grooming interactions in order to determine which types of
reciprocity, if any, best explain the data. We discuss the importance of the
temporal and micro-properties of the data in analysing reciprocity: in
particular determining the length of window over which direct reciprocity
occurs, and the importance of network-motifs in detecting patterns of indirect
reciprocity.