[Corpora-List] Open Research Position (M.S. / Ph.D. / post-doc): Analyzing Routine Activities for Crime Prediction

John D. Burger john at mitre.org
Thu Apr 24 17:27:51 CEST 2014


On Apr 22, 2014, at 05:55 , Christian Pietsch <chr.pietsch at googlemail.com> wrote:


> 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?

Yes, of course, that's exactly what it means.

- John Burger

On Apr 22, 2014, at 05:55 , Christian Pietsch <chr.pietsch at googlemail.com> wrote:


> Hi Matthew,
>
> 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:
>> Hello,
>>
>> 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
>> Threat<http://ptl.sys.virginia.edu/ptl/projects/asymmetric-threat-prediction>project);
>> 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
>> here<http://ptl.sys.virginia.edu/ptl/projects/routine-activities-analysis-for-crime-prediction>
>> .
>>
>> Sincerely,
>>
>> Matthew S. Gerber, Ph.D.
>> Research Assistant Professor
>> Department of Systems and Information Engineering
>> University of Virginia
>
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