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

机译:在线信任系统中的用户偏见:使系统设计者的意图与用户的期望保持一致

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摘要

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.
机译:社交网络的出现为融合信任的社会特征与互联网提供的技术可能性及其作为移动服务的可用性提供了无数的机会。尽管大多数计算信任模型旨在检测可信赖的实体,但对于作为系统核心的用户如何感知这些模型的关注却很少。本文研究了在用户偏见下在线信任系统的工作原理,并通过展望理论定义的偏见来分析用户行为。通过对现有系统进行实证研究,我们能够证明在线信任模型的实现目标与用户对这些模型的认知之间存在巨大差异。系统设计人员了解这种关系可以降低复杂性并改善用户体验和系统性能。结果表明,用户表现出认知偏见的趋势不仅是原因,而且是信任系统设计的结果。然后,这些结果和分析将以信任系统的Choice体系结构的形式,向系统设计人员提出一种用于用户偏爱识别和缓解的方法。

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