EAGER: Discovering Emerging Events in Social Media

社交媒体在许多领域变得越来越重要，如商业、灾难管理、科学和国家安全。在这些领域，应用程序通常必须整合社交媒体来检测正在发生的事件。然而，今天几乎没有开发出用于事件检测的解决方案，并且它们受到几个重要限制。这一探索性项目解决了这些限制，并开发了一种有效整合社交媒体以检测正在发生的事件的解决方案。该解决方案将侧重于Twitter领域，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，使其能够适应社交媒体的高速流(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。该项目将是第一个深入探索如何结合社交媒体来检测正在出现的事件的项目之一，同时考虑到社交媒体的特点。因此，这是一个高风险/高回报的项目，可以为新的研究方向打开大门，并有助于加快对社交媒体整合的研究，社交媒体整合是一个日益严重的问题，影响着社会的许多领域。如果成功，该项目还可以帮助构建能够立即产生影响的实用事件发现工具。最后，该项目将帮助培训一名为期两年的博士生，并帮助建立和发布一套基础设施工具和试验台，这些工具和试验台可以帮助PI的团队和其他社交媒体研究小组加快社交媒体整合的后续研究。项目信息将通过出版物、研讨会、教程和网站(http://www.cs.wisc.edu/~anhai/projects/event-detection.html)传播，其中将包括由此产生的研究成果、数据和系统人工制品。

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.