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In psychology and sociology, a trust metric is a measurement of the degree to which one social actor (an individual or a group) trusts another social actor. Trust metrics may be abstracted in a manner that can be implemented on computers, making them of interest for the study and engineering of virtual communities, such as Friendster and LiveJournal. Trust escapes a simple measurement because its meaning is too subjective for universally reliable metrics, and the fact that it is a mental process, unavailable to instruments. There is a strong argument〔Castelfranchi, C. and Falcone, R. (2000) Trust is much more than subjective probability: Mental components and sources of trust. Proc. of the 33rd Hawaii Int. Conf. on System Sciences (HICSS2000). Vol. 6.〕 against the use of simplistic metrics to measure trust due to the complexity of the process and the 'embeddedness' of trust that makes it impossible to isolate trust from related factors. For a detailed discussion about different trust metrics see.〔Cofta, P. (2007) Trust, Complexity and Control. Confidence in a Convergent World. J Wiley.〕 There is no generally agreed set of properties that make a particular trust metric better than others, as each metric is designed to serve different purposes, e.g.〔Ziegler, C.-N., and Lausen, G. (2005) Propagation Models for Trust and Distrust in Social Networks. Inf. Syst. Frontiers vol. 7, no. 4–5, pp. 337–358〕 provides certain classification scheme for trust metrics. Two groups of trust metrics can be identified: * Empirical metrics focusing on supporting the capture of values of trust in a reliable and standardized way; * Formal metrics that focus on formalization leading to the ease of manipulation, processing and reasoning about trust. Formal metrics can be further classified depending on their properties. Trust metrics enable trust modelling〔Marsh, S. P. (1994) (Formalising Trust as a Computational Concept ). University of Stirling PhD thesis.〕 and reasoning about trust. They are closely related to reputation systems. Simple forms of binary trust metrics can be found e.g. in PGP.〔Zimmermann, P. (1993) Pretty Good Privacy User’s Guide, Volume I and II. Distributed with the PGP software〕 The first commercial forms of trust metrics in computer software were in applications like eBay's Feedback Rating. Slashdot introduced its notion of ''karma'', earned for activities perceived to promote group effectiveness, an approach that has been very influential in later virtual communities. ==Empirical metrics== Empirical metrics capture the value of trust by exploring the behavior or introspection of people, to determine the perceived or expressed level of trust. Those methods combine theoretical background (determining what it is that they measure) with defined set of questions and statistical processing of results. The willingness to cooperate, as well as actual cooperation, are commonly used to both demonstrate and measure trust. The actual value (level of trust and/or trustworthiness) is assessed from the difference between observed and hypothetical behaviors i.e. those that would have been anticipated in the absence of cooperation. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Trust metric」の詳細全文を読む スポンサード リンク
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