HCC: Large: Social-Computational Support of Civic Engagement in Public Policymaking

这项工作的总体目标是了解并提供社会计算支持，以改善技术支持的公民参与的整个周期：（1）招募与问题有利害关系的人;（2）审议性讨论，他们在其中了解政策问题，相互接触，提出问题并叙述经验;以及（3）建立共识，参与者在此过程中进行合作内容创作，总结讨论中出现的知识，并围绕关键点达成一致。在实践中，利用社交媒体进行公民政策协商的努力往往远远达不到其创造知识和加强民主的目标。因此，迫切需要发现如何设计公民参与空间，利用社交媒体的潜力，使其不仅支持更多的参与，而且支持更好的参与，这将有利于寻求投入的决策者和参与讨论的公民。为了实现这一目标，该项目整合了社会计算系统的自然语言学习的计算机科学研究，在线社区的人机交互研究，社交媒体设计，以及动机和个人和团体审议过程的社会科学研究。这项研究将推进行为科学对个人特征与成功电子审议之间关系的理解;成功电子审议的沟通过程;以及促进从公开讨论到建立共识转变的群体过程和主持人行为。它将通过开发联合人机文本分析技术来推进自然语言处理的最新技术，以（1）促进公民在线参与政策讨论，（2）促进这种协作在线环境中的审议适度。它将通过推进推荐系统、在线社区和社交媒体研究来增加人机交互，以支持指导活动和与其他观点的互动。最后，这项工作将扩大对如何激励和支持公民更广泛、更好地参与公共决策的科学理解，这项工作将至少产生五个更广泛的影响：（1）增加对电子参与决策的理解和基础设施，并提供附加说明的公民审议数据集，供其他研究人员使用;（2）通过研究生和本科生辅导以及开发新的跨学科在线公民参与课程来加强教育;（3）通过针对初中和高中女生的计划促进STEM教育的多样性;（4）提供社区和政府外联活动;（5）通过改善公民参与一般决策造福社会。

The overarching goals of this work are to understand and to provide socio-computational support for improving the entire cycle of technology-enabled civic engagement: (1) recruitment of people with a stake in the issues; (2) deliberative discussion in which they learn about the policy issues, engage with each other, voice questions and recount experiences; and (3) consensus building in which participants move toward collaborative content-creation, summarization of the knowledge that has emerged in discussion and the development of agreement around key points. In practice, efforts to use social media for citizen policy consultations often fell far short of their knowledge-generating and democracy-reinforcing goals. There thus is a crucial need to discover how to design civic engagement spaces that leverage the potential of social media, so that they support not simply more participation but rather better participation that will benefit both the policymakers seeking input and the citizens who participate in the discussion. To achieve this goal, the project integrates computer science research on natural language learning for social-computational systems, human-computer interaction research on online communities, social media design, and social science research on motivation and individual and group deliberative processes. The research will advance behavioral science understanding of the relationship between individual characteristics and successful e-deliberation; the communicative processes that characterize successful e-deliberation; and the group processes and moderator behaviors that promote a shift from open discussion to consensus building. It will advance the state-of-the-art in natural language processing by developing joint human-computer text analysis techniques to (1) promote on-line civic engagement in policy discussions and (2) facilitate deliberative moderation in this collaborative online setting. It will add to human-computer interaction by advancing recommender systems, online communities, and social media research to support mentoring activities and engagement with alternate points of view. Finally, it will extend scientific understanding of how to motivate and support broader, better citizen participation in public policymaking.The work will have at least five broader impacts: (1) increase understanding of, and infrastructure for, e-participation in policy-making, and provide annotated datasets of civic deliberations for use by other researchers; (2) enhance education through graduate and undergraduate mentoring and development of a new interdisciplinary course on Online Civic Engagement; (3) promote STEM education diversity with programs for middle and high school girls; (4) provide community and government outreach activities; (5) benefit society by improved civic engagement in policymaking in general.