EAGER: Discovering Emerging Events in Social Media

EAGER：发现社交媒体中的新兴事件

• 批准号: 1143807
• 负责人: AnHai Doan
• 金额: $ 15万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1143807&HistoricalAwards=false
• 关键词: EAGER; Discovering; Emerging; Events; Social

Social media have become increasingly critical in many domains, such as commerce, disaster management, science, and national security. In these domains, applications often have to integrate social media to detect emerging events. Today however few solutions for event detection have been developed and they suffer from several important limitations. This exploratory project addresses these limitations and develops a solution that effectively integrates social media to detect emerging events. The solution will focus on the Twittersphere, and will address the following three key challenges: (a) how to exploit characteristics unique to social media to improve the accuracy of detecting events, (b) how to design the solutions such that they scale to high-speed streams of social media (such as 1500 tweets per second), and (c) how to leverage crowdsourcing to find truly interesting events and extract attributes of these events.The project will be among the first to explore in depth how to integrate social media to detect emerging events, taking into account social media characteristics. As such, it is a high-risk/high-payoff project that can open the door to novel research directions, and help accelerate research into social media integration, an increasingly critical problem that impacts many areas of the society. If successful, the project can also help build practical event discovery tools that can make immediate impacts. Finally, the project will help train a Ph.D. student for two years, and help build and release a set of infrastructure tools and testbeds that can help accelerate subsequent research into social media integration, for both the PI's group and other research groups in social media. The project information will be disseminated via publications, workshops, tutorials, and the Web site (http://www.cs.wisc.edu/~anhai/projects/event-detection.html) that will include the resulting research results, data and system artifacts.

社交媒体在商业、灾害管理、科学和国家安全等许多领域变得越来越重要。在这些领域中，应用程序通常必须集成社会媒体来检测新出现的事件。然而，目前已经开发的事件检测解决方案很少，而且它们受到几个重要的限制。这个探索性项目解决了这些限制，并开发了一个解决方案，有效地整合了社交媒体来检测新兴事件。该解决方案将专注于Twittersphere，并将解决以下三个关键挑战：(a)如何利用社交媒体的独特特征来提高检测事件的准确性，(b)如何设计解决方案，使其可扩展到社交媒体的高速流（例如每秒1500条推文），以及(c)如何利用众包来发现真正有趣的事件并提取这些事件的属性。该项目将是首批深入探索如何结合社交媒体特点，整合社交媒体来检测新兴事件的项目之一。因此，这是一个高风险/高回报的项目，可以打开新的研究方向的大门，并有助于加速对社会媒体整合的研究，这是一个日益关键的问题，影响着社会的许多领域。如果成功，该项目还可以帮助构建可以立即产生影响的实用事件发现工具。最后，该项目将帮助培养一名博士生为期两年，并帮助建立和发布一套基础设施工具和测试平台，这些工具和测试平台可以帮助PI的团队和其他社交媒体研究团队加速后续对社交媒体集成的研究。项目信息将通过出版物、讲习班、教程和网站（http://www.cs.wisc.edu/~anhai/projects/event-detection.html）传播，其中将包括最终的研究结果、数据和系统工件。