CAREER: Novel Approaches for Reasoning about Local Communities from Social Awareness Streams Data

职业：从社会意识流数据推理当地社区的新方法

• 批准号: 1446374
• 负责人: Mor Naaman
• 金额: $ 34.89万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1446374&HistoricalAwards=false
• 关键词: CAREER; Novel; Approaches; Reasoning; about

This project will examine temporal, social, and geographic patterns in large-scale social awareness streams (SAS) data for local communities. SASs, such as Twitter and Facebook, are radically altering our society's information fabric. These new communication platforms are used by millions of people to share brief status messages in socially connected public forums. These messages expose vast amounts of data from, and about, local geographic communities -- data that reflect people's activities, interests, and attention, in thousands of localities worldwide. Using this vast and still emerging sources of data, this research program will make SAS into a viable and significant source of information with capacity to transform our understanding of local communities. As a first activity, the research will adapt algorithms from other fields to identify temporal patterns in SAS data that are stable across multiple communities. Importantly, the work will reason about how and when these patterns break. For example, SAS data may expose sleeping patterns in a community, and help identify mass anxiety when these patterns break. Further, the project will develop methods to identify differences in SAS patterns between local communities, and connect these findings to other sources of data. Next, the research will develop methods to compare how different groups (e.g., by age or ethnicity) use specific neighborhoods and cities. Finally, the work will examine the relations between local communities and network ties as reflected in SAS data. The findings will form the basis for developing novel models of computation for SAS systems, and inform the creation of tools and applications geared to re-imagine SAS as reliable information systems for local communities. The project is rooted in social computing and in human-centered approaches to development of new technology. As such, the work entails interdisciplinary investigation using methods and research questions drawing on fields as diverse as information and computer science, sociology, and communication. The project will tackle significant information challenges that these SAS and other social computing platforms present, such as the scale, bias, and the increasing amount of noise and spam, as well as the brevity and lack of context of posted messages. The research will develop novel methods and approaches to using these new information sources to extract knowledge about, and for, local communities. The research focus on social media and local communities lends itself well to outreach and education activities. The outreach efforts will enhance the connection of public libraries to the communities they serve, and relate the social media experiences of people?s everyday lives to scientific challenges. Participatory design workshops and visits to select educational institutions will engage individuals currently underrepresented in the sciences. An interdisciplinary education program will prepare a diverse set of students at all levels to lead the next generation of innovation, research, and education in socio-technical systems. Finally, this project will have a significant impact on our society. By leveraging SAS as novel sources of information, the research will lay the foundation for new studies about local communities. The resulting technologies and insights will inform and transform the work of local governments, news organizations, planners, and researchers, as well as local residents and activists, allowing them to take full advantage of these new repositories of human expression and thought with relevance to such diverse social challenges as emergency response, resource planning, and public health.

该项目将研究当地社区的大规模社会意识流（SAS）数据中的时间，社会和地理模式。 Sass，例如Twitter和Facebook，正在从根本上改变我们社会的信息结构。这些新的通信平台被数百万人使用，以在社会联系的公共论坛中分享简短的状态信息。这些信息暴露了当地地理社区的大量数据 - 在全球成千上万的地区反映了人们的活动，兴趣和关注的数据。使用这种庞大而仍在新兴的数据来源，该研究计划将使SAS成为可行且重要的信息来源，具有改变我们对当地社区的理解的能力。作为第一次活动，该研究将适应其他领域的算法，以识别在多个社区之间稳定的SAS数据中的时间模式。重要的是，这项工作将推理这些模式如何以及何时破裂。例如，SAS数据可能会暴露社区中的睡眠模式，并在这些模式破裂时有助于确定大规模焦虑。此外，该项目将开发方法来识别当地社区之间SAS模式的差异，并将这些发现与其他数据源联系起来。接下来，该研究将开发方法来比较不同群体（例如，按年龄或种族）如何使用特定的社区和城市。最后，这项工作将检查当地社区和网络关系之间的关系，如SAS数据中所示。这些发现将构成为SAS系统开发新型计算模型的基础，并告知创建用于重新想象SAS作为当地社区可靠信息系统的工具和应用程序的创建。该项目植根于社会计算和以人为本的新技术发展方法。因此，这项工作需要使用诸如信息和计算机科学，社会学和沟通等多样化的领域的方法和研究问题进行跨学科的调查。该项目将应对这些SAS和其他社交计算平台所存在的重要信息挑战，例如规模，偏见，噪音和垃圾邮件的增加，以及已发布消息的简洁性和缺乏上下文。该研究将开发出新的方法和方法，用于使用这些新信息源来提取有关当地社区的知识和对当地社区的知识。该研究的重点是社交媒体和当地社区，非常适合外展和教育活动。推广工作将加强公共图书馆与他们所服务的社区的联系，并将人们的日常生活社交媒体经验与科学挑战联系起来。参与性的设计研讨会和访问选择教育机构将与当前在科学中不足的人与个人联系。跨学科的教育计划将准备各个级别的各种学生，以领导下一代社会技术系统中的创新，研究和教育。最后，该项目将对我们的社会产生重大影响。通过利用SAS作为新的信息来源，该研究将为有关当地社区的新研究奠定基础。由此产生的技术和见解将为地方政府，新闻机构，计划者和研究人员以及当地居民和激进主义者的工作提供信息和改变，使他们能够充分利用这些新的人类表达和思想库存库，与诸如紧急响应，资源计划和公共健康等多样化的社会挑战相关。