SGER: WebTrack - Learning Geographical Movements of Social Networks through the Web

SGER：WebTrack - 通过网络学习社交网络的地理运动

• 批准号: 0628792
• 负责人: Sheila Tejada
• 金额: $ 9.42万
• 依托单位: Tulane University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-04-01 至 2007-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0628792&HistoricalAwards=false
• 关键词: SGER; WebTrack; Learning; Geographical; Movements

Hurricane Katrina disrupted many social networks. Over 1.5 million people evacuated New Orleans. Companies, schools, and families were geographically separated after the storm, and they needed to rediscover the locations of their members. A "burst" of new data sources, generated on the web by disaster relief organizations, news outlets, employers, and hurricane survivors, aided those affected by the storm in searching for members of their social groups. This project investigates methods to automate tracking the geographical movements of social networks using the variety of information sources available on the web. As more time passes from Hurricane Katrina, these sources become increasingly inaccessible; therefore, the first step is to quickly harvest these Katrina-related blogs and forums, survivor databases and websites. Next, this project explores new link analysis techniques that utilize these new heterogeneous data sources to track the geographical movement of the network members, given information about the social networks prior to the disruption. These new techniques combine previous work in social network analysis, based on the study of the patterns of connections between members or subgraphs in a social networks, and link analysis methods, which determine whether a connection or link exist between members. The project will result in a range of broader impacts. The project will aid in harvesting and archiving Hurricane Katrina-related highly perishable data that will provide a historical record of the disaster. The resulting information resource will allow researchers to access an extensive dataset to develop new research in social networks and disaster recovery. The new link analysis developed in this project will assist in automating the social network reconnection task for Hurricane Katrina victims and make us better prepared to handle future disasters. The project Web site (http://www.eecs.tulane.edu/tejada/katrina) provides access to more information about the research and the results.

卡特里娜飓风破坏了许多社交网络。超过150万人撤离新奥尔良。公司、学校和家庭在风暴之后被地理上分开，他们需要重新找到他们的成员的位置。救灾组织、新闻媒体、雇主和飓风幸存者在网络上产生了大量新的数据源，帮助那些受风暴影响的人寻找他们的社会群体成员。该项目研究了利用网络上的各种信息源自动跟踪社交网络的地理移动的方法。随着卡特里娜飓风的时间越来越长，这些来源变得越来越难以访问;因此，第一步是快速收集这些与卡特里娜飓风相关的博客和论坛，幸存者数据库和网站。接下来，该项目探讨了新的链接分析技术，利用这些新的异构数据源来跟踪网络成员的地理移动，在中断之前提供有关社交网络的信息。这些新技术结合了联合收割机以前在社会网络分析中的工作，基于对社交网络中成员或子图之间的连接模式的研究，以及确定成员之间是否存在连接或链接的链接分析方法。该项目将产生广泛的影响。该项目将帮助收集和存档与卡特里娜飓风有关的易腐数据，这些数据将提供灾难的历史记录。由此产生的信息资源将使研究人员能够访问广泛的数据集，以开发社交网络和灾难恢复方面的新研究。该项目开发的新链接分析将有助于自动化卡特里娜飓风受害者的社交网络重新连接任务，并使我们更好地准备应对未来的灾难。该项目的网站（http：//www.eecs.tulane.edu/tejada/katrina）提供了关于研究和结果的更多信息。