Two agent-based models of trust in social networks : a thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Psychology

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Massey University
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Trust is a pervasive feature of human social interaction. Much of the recent interest in trust has been at the level of individuals and dyads. But trust is also important in networks, as it enables the formation and maintenance of social cooperation. Understanding this requires an understanding of how trust arises, functions, and is maintained within networks of people. Developing understandings of how individual behaviours aggregate, and how they evolve within an environment that includes other individuals developing similar behaviours is a difficult task. One way that it may be approached is through computer simulation using agent-based models. This thesis describes the development of two agent-based models of trust. Agent-based modelling is a novel method within the discipline of social psychology. The thesis first describes what agent-based modelling is, describes some of the situations in which it might be applicable, discusses how it might apply to modelling individuals in a social setting, and discusses the experience of developing the model. The first model was based on a theoretical cognitive model of behaviour within a particular formal game that has been claimed to involve trust, the Investor Game. This model showed that a population in which all individuals are are pursuing similar optimal strategies does not generate any of the interesting behaviours that we would expect to see in real-world interactions involving trust and cooperation. This tends to suggest that modelling trust behaviours also requires modelling behaviours that are untrustworthy, and representing a full range of potential behaviours, including outliers. The second model is based on a more naturalistic setting, on-line peer-to-peer trading through sites such as New Zealand's Trade Me, or eBay. In this model, individual traders carry characteristics that determine their reliability and honesty, and attempt to find effective strategies for identifying other traders' trustworthiness. This model suggests that, while providing traders with minimal guidance on strategies and allowing them to search for the best strategies may result in them finding effective strategies, this is not the only possible outcome. Somewhat surprisingly, effective trust strategies acted to contain unreliability, rather than dishonesty.
Trust, Social networks, Intelligent agents (Computer software), Human behaviour, Computer simulation