[CSENews] MSU CSE Lecture Series: Spatiotemporal Crime Prediction using GPS- and Time-Tagged Tweets, Dr. Matt Gerber, Friday, Nov 8st, 11:00am in 3105 EB

[Teresa Isela VanderSloot]

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*Spatiotemporal Crime Prediction using GPS- and Time-Tagged Tweets*
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*Dr. Matt Gerber*
*Department of Systems and Information Engineering *
*University of Virginia *
*Friday, Nov 8st, 11:00am in 3105 EB*
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Abstract:
Recent research has shown that social media messages (e.g., tweets) can 
be used to predict various large-scale events like elections (Bermingham 
and Smeaton, 2011), infectious disease outbreaks (St. Louis and Zorlu, 
2012), and even national revolutions (Howard et al., 2011). The 
essential hypothesis is that the timing, location, and content of these 
messages are informative with regard to such future events. For many 
years, the Predictive Technology Laboratory at the University of 
Virginia has been constructing statistical prediction models of criminal 
incidents (e.g., robberies and assaults), and we have recently found 
preliminary evidence of Twitter’s predictive power in this domain (Wang, 
Brown, and Gerber, 2012). In my talk, I will present an overview of our 
crime prediction research with a specific focus on current Twitter-based 
approaches. I will discuss (1) how precise locations and times of tweets 
have been integrated into the crime prediction model, and (2) how the 
textual content of tweets has been integrated into the model via latent 
Dirichlet allocation. I will present current results of our research in 
this area and discuss future areas of investigation.

Bio:
Matthew Gerber joined the University of Virginia faculty in 2011 and is 
currently a Research Assistant Professor in the Department of Systems 
and Information Engineering. Prior to joining the University of 
Virginia, he was a Ph.D. candidate in the Department of Computer Science 
and Engineering at Michigan State University and a Visiting Instructor 
in the School of Computing and Information Systems at Grand Valley State 
University. In 2010, he received (jointly with Joyce Chai) the ACL Best 
Long Paper Award for his work on recovering null-instantiated arguments 
for semantic role labeling. His current research focuses on the semantic 
analysis of natural language text and its application to various 
prediction and informatics problems.

Host:
Dr. Joyce Chai

-------------------------
Dr. Xiaoming Liu

Assistant Professor
Department of Computer Science and Engineering
Michigan State University



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