HCC: Informing Social Translucence with Open Composable Online Reputation Systems

大型的、分布式的、用户贡献的内容网站，如博客、网络论坛、Slashdot和维基百科，已经显著改变了大众在线社交互动的特征。当个人参与时，他们的行为对其他参与者可见。检查准备内容和维护社区的工作是理解这些系统的本质的关键。社交互动是一个概念框架，用于思考在线社区中的社交行为如何促进未来的社交互动。信誉系统，代表在线社区中参与者的信誉的系统，在电子商务领域已经得到了很好的研究。然而，设计和开发广义声誉系统的理论原则或指导方针还没有出现。拟议的研究将回答四个关键问题之间的关系声誉系统和现有的框架的社会连贯性：社会连贯性如何框架的发展反思社会系统？什么样的方法来分解“声誉”的组成部分，以反映在线社区中所有有价值的活动？ 哪些技术方法有效地收集、挖掘或引出与个人声誉的具体方面有关的数据？如何建立系统，使个人能够了解他们的声誉，因为它是由社区的其他成员收集和解释？直到最近，开发一个声誉系统来阐述社会责任的框架还是非常困难的。但是，像维基百科这样的大型社区数据集的可访问性减轻了一个主要的绊脚石，即数据的可用性。智力价值：拟议的研究将扩展社会连贯性，作为社会和协作系统的设计和开发的框架。分布式贡献者社区的开发人员能够构建可由社区占用的声誉系统，这将通过使用社会透明度来说明。最后，这些结果将开发一个位于分布式贡献者社区的声誉模型-一个看到大部分的在线工作活动的一部分，社区成员的reputation.Broader的影响：主要的贡献将是一个不断增长的多样性的分布式贡献者在线社区的互动，贡献和意义的改善。随着越来越多的人参与在线社区，互动和信任的水平受到参与者彼此信息量的限制。有效地支持这些社区是社会计算的一个重要挑战。所提出的方法将社会半透明的工具交给社区--那些最有能力创造、反映、辩论和完善社会半透明行为表现的人。

Large, distributed, user-contributed content sites like blogs, web forums, Slashdot and Wikipedia, have significantly changed the character of mass social interaction online. As individuals participate, their actions are visible to other participants. Examining the work of both preparing content and maintaining the community is key to understanding the nature of these systems. Social translucence is a conceptual framework for thinking about how social actions in an online community facilitate future social interaction. Reputation systems, systems that represent the reputation of participants in an online community, have been well studied in the domain of e-commerce. However, theoretical principles or guidelines to designing and developing generalized reputation systems have not emerged. The proposed research will answer four critical questions about the relationship between reputation systems and the existing framework of social translucence: How can social translucence frame the development of reflective social systems? What methods unpack the components of "reputation" to reflect the full range of valued activities in an online community? What technical methods effectively collect, mine or elicit data related to specific dimensions of an individual's reputation? How can systems be built that enable individuals to understand their reputation as it is collected and interpreted by other members of the community? Until recently developing a reputation system to elaborate the framework of social translucence was prohibitively difficult. But the accessibility of large community datasets, like that of Wikipedia, has mitigated one major stumbling block, the availability of data.Intellectual merit: The proposed research will extend social translucence as a framework for the design and development of social and collaborative systems. The ability of developers of distributed contributor communities to build reputation systems that can be appropriated by the community will be illustrated through the use of social translucence. Lastly, these results will develop a situated model of reputation in distributed contributor communities - one that sees a majority of online work activity as part of a community member's reputation.Broader impacts: The primary contribution will be an improvement in the interaction, contribution and sense-making of the ever growing diversity of distributed contributors to online communities. As more people participate in online communities, the level of interaction and trust is limited by the amount of information that participants have about one another. Effectively supporting these communities is an important challenge of social computing. The proposed approach puts socially translucent tools in the hands of the community - those who are in the best position to create, reflect, debate and refine socially translucent representations of behavior.