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Systematic Measurement of Centralized Online Reputation Systems.

机译:集中式在线信誉系统的系统度量。

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摘要

Background. Centralized online reputation systems, which collect users' opinions on products, transactions and events as reputation information then aggregate and publish it, have been widely adopted by Internet companies. These systems can help users build trust, reduce information asymmetry and filter information.;Aim. Much research in the area has focused on analyzing single type systems and the cross-type evaluation usually concentrates on one aspect of the system. This research proposes a systematic evaluation model (SERS) that can measure different types of reputation system.;Method. From system perspective, all reputation systems can be divided into five underlying components. Input refers to the collection of ratings and reviews; Processing is the aggregation of ratings. Output publishes the information. Feedback Loop is the collection of the feedback of the review, which can be seen as the 'review of the review'; Finally, Storage stores all the information. Therefore, based on each component's characteristics, a series of benchmark criteria can be defined and incorporated into the model.;Results. The SERS has defined 29 criteria, which can compare and measure different aspects of reputation systems. The model was theoretically assessed on its coverage of the successful factors of reputation systems and the technical dimensions of information systems. The model has also been empirically assessed by applying it to 15 commercial sites.;Conclusion. The results obtained indicated that the SERS model has identified most important characteristics that have been proposed by reputation systems literature. In addition the SERS has covered most dimensions of the two basic technical information system measurements: information quality and system quality. The empirical assessment has shown that the SERS can evaluate different types of reputation systems and is capable of identifying the weakness of current systems.
机译:背景。互联网公司已广泛采用集中式在线信誉系统,该系统收集用户对产品,交易和事件的意见,并将其作为信誉信息,然后进行汇总和发布。这些系统可以帮助用户建立信任关系,减少信息不对称并过滤信息。该领域的许多研究都集中在分析单一类型的系统上,而交叉类型的评估通常集中在系统的一个方面。本研究提出了一种可以评估不同类型信誉系统的系统评价模型。从系统角度来看,所有信誉系统都可以分为五个基本组件。输入是指评级和评论的集合;处理是收视率的汇总。输出发布信息。反馈循环是评论的反馈的集合,可以看作是“评论的评论”;最后,Storage存储所有信息。因此,根据每个组件的特征,可以定义一系列基准标准并将其纳入模型。 SERS定义了29条标准,可以比较和衡量声誉系统的不同方面。从理论上对模型进行了评估,评估模型涵盖了声誉系统的成功因素和信息系统的技术范围。该模型还通过将其应用于15个商业站点进行了经验评估。获得的结果表明,SERS模型已经确定了信誉系统文献所提出的最重要的特征。此外,SERS还涵盖了两个基本技术信息系统度量的大部分维度:信息质量和系统质量。实证评估表明,SERS可以评估不同类型的信誉系统,并且能够识别当前系统的弱点。

著录项

  • 作者

    Liu, Ling.;

  • 作者单位

    University of Durham (United Kingdom).;

  • 授予单位 University of Durham (United Kingdom).;
  • 学科 Information Technology.;Web Studies.;Computer Science.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 160 p.
  • 总页数 160
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自然科学史;
  • 关键词

  • 入库时间 2022-08-17 11:44:58

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