so you want to build a heuristic precrime detector based on routine activities observed on social networks. Does that mean that if, say, I tend to update my status at the same time as some terrorist in your training set, your software will label me as a likely terrorist and put me on a no-fly list? Will I get a chance to prove my innocence?
When you have some spare time, try to watch Minority Report. Or did this movie inspire your project? Then you must have misunderstood its message.
Your suspect Christian
On Mon, Apr 21, 2014 at 11:34:11AM -0400, Matthew Gerber wrote:
> A new research position has opened within our lab, and we are seeking M.S.,
> Ph.D., and post-doc researchers.
> One-sentence summary: We are mining social media for indicators of
> individual routine activities for the purpose of improved crime prediction.
> Longer summary: This project focuses on the spatiotemporal prediction of
> localized attacks carried out against individuals in urban areas. We view
> an attack as the outcome of a point process governed by the interaction of
> attackers, targets, and the physical environment. Our ultimate goal is to
> predict future outcomes of this process in order to increase the security
> of human populations and U.S. assets and interests. However, achieving this
> goal requires a deeper understanding of how attack outcomes correlate with
> the routine activities of individuals in an area. The proposed research
> will generate this understanding and in doing so will answer questions such
> as the following: What are the dimensions along which individuals’
> activities should be quantified for the purpose of attack prediction? How
> can measurements along these dimensions be taken automatically and with
> minimal expense (e.g., via social media)? What are the implications of such
> measurements for attack prediction performance? Subsuming these questions
> is the issue of geographic variation: do our answers change when moving
> from a major U.S. city to a major U.K. city? There has been plenty of
> previous work on spatiotemporal attack prediction (see our Asymmetric
> however, these basic questions remain unanswered, leaving a
> substantial gap in our understanding of attack processes and their
> relationships with individuals’ routine activities.
> More information can be found
> Matthew S. Gerber, Ph.D.
> Research Assistant Professor
> Department of Systems and Information Engineering
> University of Virginia
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