Dr. James Caverlee, associate professor of computer science and engineering at Texas A&M University, was chosen by the Google Faculty Research Awards Program as a recipient of financial support for his proposal in the social media category, "Modeling and Inferring Local Expertise." This research is a collaborative effort with professor Daniel Z. Sui, chair of the geography department at The Ohio State University.
"The goal of this research project is to investigate techniques and develop effective tools for modeling and automatically inferring local expertise in large-scale social media," said Caverlee. "Local experts — in contrast to general topic experts — have specialized knowledge focused around a particular location, and are critical for many applications including answering local information needs and interacting with community experts. And yet identifying these experts is difficult.
"To successfully identify and infer local expertise, this project proposes a flexible local expertise framework that integrates both a person's topical expertise and their local authority by exploiting the fine-grained publicly-shared GPS coordinates of millions of social media users.
Caverlee added, "The hoped for result of this research is that it will lead to important research advances for assessing local expertise, enabling new opportunities for local and map-based search, results re-ranking by local expertise, and expert-driven analytics."
The project is one of 110 chosen from a total of 722 considered by Google during its Summer 2014 call for research project proposals. Google Research Award support is for one year and includes the basic expenses for one graduate student.
Caverlee joined the computer science and engineering faculty at Texas A&M in 2007 after receiving a doctoral degree in computer science from the College of Computing at the Georgia Institute of Technology. This is the third time since 2008 that Caverlee has received the Google Faculty Research Award. His many honors also include the College of Engineering Caterpillar Teaching Excellence Award for 2013-2014, Texas A&M Computer Science Undergraduate Faculty Teaching Award (2013), NSF Faculty Early CAREER award in 2012, Air Force Office of Scientific Research-Young Investigator Program (AFOSR-YIP) grant (2012), Center for Teaching Excellence Montague-CTE Scholar award (2011), 2010 Defense Advanced Research Projects Agency Young Faculty Award (DARPA YFA), and Graduate Faculty Teaching Excellence Award (2009 and 2010).