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Seminar on Towards Real-Time Crowd-Oriented Search and Computation

March 9, 2012 @ 3:00 pm - 4:00 pm

Room 1037 (Emerging Technology Building- ETB)


Online communities are the fastest growing phenomena on the Web, enabling millions of users to discover and explore community-based knowledge spaces. While long-lived communities have been one of the key organizing principles of these systems, there is widespread evidence of highly-dynamic, ad-hoc crowd formation in existing social systems. Examples range from users posting to Facebook in response to a live Presidential debate, to users sharing pictures about a chemical fire at a nearby refinery, to blog commenting about breaking news, and so on.  These crowds are dynamically formed and potentially short-lived, often with only implicit signals of their formation at all. Identifying these highly-dynamic crowds from the massive scale of the real-time web, monitoring their quality, and connecting stakeholders to these crowds in real-time could revolutionize the decision-making of critical stakeholders. Unfortunately, existing search solutions cannot be directly applied to nascent crowds, leaving a significant research gap. In this talk, I will highlight our work towards developing real-time crowd-oriented search and computation systems, so that high-value stakeholders can monitor, analyze, and distill high-quality information from bursty social systems and actively engage with the crowds generating this information.

Bio:  Prof. James Caverlee is currently a tenure-track faculty member in the department of Computer Science and Engineering at Texas A&M University. At Texas A&M, Dr. Caverlee directs the infolab, a research lab founded in 2007 to study problems at the intersection of web-scale information management, distributed data-intensive systems, and social computing. His overall research goal is to develop algorithms and systems to enable efficient and trustworthy information sharing and knowledge discovery over dynamic, heterogeneous, and massive-scale networked information systems. Dr. Caverlee received his Ph.D. from Georgia Tech in 2007, M.S. degrees in Computer Science (2001) and in Engineering-Economic Systems & Operations Research (2000) from Stanford University, and a B.A. in Economics from Duke University (1996, magna cum laude). Dr. Caverlee is a recipient of the 2010 Defense Advanced Research Projects Agency (DARPA) Young Faculty Award, the 2012 Air Force Office of Scientific Research (AFOSR) Young Investigator Award, a 2012 NSF CAREER Award, and has been named a Texas A&M Center for Teaching Excellence Montague-CTE Scholar for 2011-2012.



March 9, 2012
3:00 pm - 4:00 pm