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 (www.cs.wisc.edu/~anhai/projects/event-detection.html) that will include the resulting research results, data and system artifacts.
