III: Small: Collaborative Research: Detection and Presentation of Community and Global Event Content from Social Media Sources

Twitter、Facebook、YouTube和Flickr等社交媒体网站托管着越来越多的用户内容，这些内容与现实世界的事件有关，从总统就职典礼到社区特定事件。不幸的是，现有的用于查找、组织和呈现与事件相关的社会媒体内容的工具非常有限。该项目将解决关键的端到端信息处理和呈现方法，这些方法将改变公众从社交媒体来源获取现实世界事件信息的方式。特别是，这项工作将增加目前代表性不足的社区的数字存在，并解决他们的信息需求：对于这些社区来说，主流媒体通常不会报道事件，但越来越多地可以在社交媒体服务上获得。作为一个独特的特点，该项目将利用几个研究领域，即信息检索和数据库，人机交互和社会媒体，从而有助于培养多学科的学生。pi将继续包括本科生和来自研究中代表性不足人群的学生。该项目将为基于事件的信息任务提供新的数据分析和可视化技术，解决社会媒体系统中的人为和计算因素，以处理大量嘈杂的、用户贡献的、结构和质量差异很大的内容。为了有效地浏览、搜索和呈现事件内容，这项工作将利用丰富的社交媒体文档来解决几个基本问题。第一个问题是在社交媒体内容存储库中检测事件。这些内容越来越多地由用户实时发布，它们是嘈杂和高度异构的，但可以帮助早期发现各种规模的大范围事件。第二个问题是对与检测到的或已知的事件相关的内容的全面识别，这些内容目前分散在社交媒体网站上，通常很难找到和收集。第三个问题是内容表示，这需要为社交媒体事件内容开发新颖的表示和可视化技术。即使是单个事件的可用内容数量也可能是压倒性的，并阻碍数据探索和意义构建。该项目将创造新的工具来改变事件信息的观看体验。这些工具将允许用户创建和共享事件数据的个性化视图，作为一种讲故事的实践。最后，作为主要成果，研究中使用的数据将尽可能提供给其他研究人员。此外，另一个主要成果将是基于这项研究的公开可用的原型系统，旨在帮助将计算和信息科学挑战与各种用户的活动和自然兴趣联系起来。

Social media sites such as Twitter, Facebook, YouTube, and Flickr host an ever-increasing amount of user content captured or produced in association with real-world events, from presidential inaugurations to community-specific events. Unfortunately, the existing tools to find, organize, and present the social media content associated with events are extremely limited. This project will address critical end-to-end information processing and presentation methods that will transform public access to real-world event information from social media sources. In particular, this work will increase the digital presence of currently underrepresented communities and address their information needs: for these communities, events are often not covered by mainstream media, but are increasingly available on social media services. As a distinctive characteristic, the project will draw on several research areas, namely, information retrieval and databases, human-computer interaction, and social media, thus contributing to educating multidisciplinary students. The PIs will continue to include undergraduate students and students from underrepresented populations in the research.The project will result in new data analysis and visualization techniques for event-based information tasks, addressing human and computational factors in social media systems to handle vast collections of noisy, user-contributed content of widely varying structure and quality. To enable effective browsing, search, and presentation of event content, this work will use the wealth of social media documents to address several fundamental problems. The firstproblem is the detection of events in repositories of social media content. Such content, increasingly posted by users in real time, is noisy and highly heterogeneous, but can help in the early detection of a wide range of events of all sizes. The second problem is the comprehensive identification of content related to detected or known events, currently fragmented across social media sites and often hard to find and collect. The third problem is content presentation, which requires the development of novel presentation and visualization techniques for social media event content. The amount of contentavailable even for a single event can be overwhelming and hinder data exploration and sense-making. The project will create new tools that will transform the viewing experience of the event information. These tools will allow users to create and share personalized views of the event data as a story-telling practice. Finally, as a main outcome, the data used in the research will be made available to other researchers whenever possible. Moreover, another main outcome will be a publicly available prototype system based on this research, designed to help connect computing and information science challenges to the activities and natural interests of a diverse set of users.