HCC: Medium: Personalized information access for online deliberation systems

在线审议旨在通过获取不同的专业知识和经验，在富有成效的思想交流中提供信息和整理证据，来改进群体决策。成功的讨论环境可以带来巨大的好处，比如扩大参与，利用更广泛的知识，相互检验想法，以及培养对其他观点的欣赏。然而，对于引起广泛讨论的大而复杂的问题空间，潜在参与者很难找到他们最能做出贡献的地方，很难理解各种贡献是如何结合在一起的，也很难把握需求和贡献之间的偶然性。为了解决这个问题，这个项目将开发和测试一个系统，该系统提供一个大型信息空间的个性化视图，以反映每个用户的目标、专业知识和兴趣的方式揭示贡献的形状和重点。该系统将使参与者能够看到他们的目标和兴趣如何与当前的主题相匹配，并找到感兴趣的人员群体和相关的贡献集。为此，该研究将结合社会语言学的见解和语言技术领域最先进的潜变量建模技术，扩展先前在视角和立场建模领域的工作，以便识别文本数据中的必要结构，从而实现个性化信息提取、摘要和呈现。该项目包括进行档案数据分析以开发算法和数据表示法，进行实验以测试各种表示主题和社交网络的方式对用户的价值，分阶段进行一系列部署以进行形成性和总结性评估，以及开发工具体系结构和用户界面以支持试验和部署。通过这些活动，调查人员将系统地探索设计决定对参与、通航和审议性质的影响。

Online deliberation seeks to improve group decision making by accessing diverse expertise and experience, informing and marshaling evidence in a fruitful exchange of ideas. Successful deliberation environments can bring great benefits, such as broadening participation, tapping a greater range of knowledge, testing ideas against each other, and fostering appreciation of other views. However, for large and complex problem spaces that generate extensive discussion, it is difficult for would-be participants to find where they could best make a contribution, to understand how various contributions fit together, or to grasp the contingencies between needs and contributions. To address this problem, this project will develop and test a system that provides a personalized view of a large information space that reveals the shape and foci of contributions in a way that reflects the goals, expertise, and interests of each user. The system will allow participants to see how their goals and interests match current themes and to find groups of people and related sets of contributions that would be of interest. To do this, the research will integrate insights from sociolinguistics with state-of-the-art latent variable modeling techniques from the field of language technologies to extend prior work in the areas of perspective and stance modeling in order to identify the necessary structure in textual data to enable personalized information extraction, summarization, and presentation. The project includes archival data analysis to develop algorithms and data representations, experiments to test the value to users of various ways of representing topics and social networks, a staged series of deployments for formative and summative evaluation, and the development of tool architecture and user interfaces to support experimentation and deployment. Through these activities, the investigators will systematically explore the effects of design decisions on participation, navigability and the nature of the deliberation.