Social media sites such as Twitter, Facebook, YouTube, and Flickr host an ever-increasing amount of user content captured or produced in association with real-world events, from presidential inaugurations to community-specific events. Unfortunately, the existing tools to find, organize, and present the social media content associated with events are extremely limited. This project will address critical end-to-end information processing and presentation methods that will transform public access to real-world event information from social media sources. In particular, this work will increase the digital presence of currently underrepresented communities and address their information needs: for these communities, events are often not covered by mainstream media, but are increasingly available on social media services. As a distinctive characteristic, the project will draw on several research areas, namely, information retrieval and databases, human-computer interaction, and social media, thus contributing to educating multidisciplinary students. The PIs will continue to include undergraduate students and students from underrepresented populations in the research.

The project will result in new data analysis and visualization techniques for event-based information tasks, addressing human and computational factors in social media systems to handle vast collections of noisy, user-contributed content of widely varying structure and quality. To enable effective browsing, search, and presentation of event content, this work will use the wealth of social media documents to address several fundamental problems. The first problem is the detection of events in repositories of social media content. Such content, increasingly posted by users in real time, is noisy and highly heterogeneous, but can help in the early detection of a wide range of events of all sizes. The second problem is the comprehensive identification of content related to detected or known events, currently fragmented across social media sites and often hard to find and collect. The third problem is content presentation, which requires the development of novel presentation and visualization techniques for social media event content. The amount of content available even for a single event can be overwhelming and hinder data exploration and sense-making.

The project will create new tools that will transform the viewing experience of the event information. These tools will allow users to create and share personalized views of the event data as a story-telling practice. Finally, as a main outcome, the data used in the research will be made available to other researchers whenever possible. Moreover, another main outcome will be a publicly available prototype system based on this research, designed to help connect computing and information science challenges to the activities and natural interests of a diverse set of users.

Agency
National Science Foundation (NSF)
Institute
Division of Information and Intelligent Systems (IIS)
Application #
1017845
Program Officer
Sylvia Spengler
Project Start
Project End
Budget Start
2010-09-15
Budget End
2014-06-30
Support Year
Fiscal Year
2010
Total Cost
$249,928
Indirect Cost
Name
Rutgers University
Department
Type
DUNS #
City
Piscataway
State
NJ
Country
United States
Zip Code
08854