User bias in online trust systems: aligning the system designers’ intentions with the users’ expectations

The advent of social networks opened a myriad opportunities for merging the social character of trust with the technical possibilities offered by the Internet and its availability as a mobile service. While most of the computational trust models aim to detect trustworthy entities, much less attention is paid to how these models are perceived by the users who are the core of the system. This paper delves into the workings of online trust systems under user bias and analyses the user behaviour through biases defined by Prospect theory. By performing empirical study on an existing system, we are able to demonstrate that there is a huge discrepancy between the aim of implementation of the online trust models and the users’ perception of those models. Understanding of this relation by the system designers can reduce complexity and improve the user experience and the system performance. The results imply that the tendency of the users to exhibit cognitive biases is not only the cause, but also the effect from the trust system design. These results and the analysis are then used to propose to the system designers a methodology for user bias identification and mitigation in the form of a Choice architecture for trust systems.