Social Media affects the Timing, Location, and Severity of School Shootings
Javier Garcia-Bernardo
J. Garcia-Bernardo, H. Qi, J. M. Shultz, A. M. Cohen, N. F. Johnson, P. S. Dodds
http://arxiv.org/abs/1506.06305
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/3022372/logo_1200_white.png)
Dec 14th, 2012: Sandy Hook ATTACK.
Since then: 194 school shootings.
Visualization: https://everytownresearch.org/school-shootings
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993575/Screenshot_from_2016-09-11_20-30-05.png)
Visualization: https://everytownresearch.org/school-shootings
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993569/Screenshot_from_2016-09-11_20-28-33.png)
Visualization: https://everytownresearch.org/school-shootings
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993570/Screenshot_from_2016-09-11_20-28-38.png)
Do school shootings cluster in time?
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/3017466/d2.png)
DATA description: clustering
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/3017468/d4.png)
DATA description: heavy TAILS
Do school shootings cluster in space?
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/3017454/h2.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/3017455/h1.png)
Do school shootings affect the timing of new attacks?
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993628/descr.png)
Do school shootings affect the timing of new attacks through media?
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993645/twitter.png)
Copycat effect
can we model all this?
FIRST model
RED VERSuS BLUE
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993622/latex_802d0c0383c789c1dac8fa0fc580c7ad.png)
N. F. Johnson, et al., Scientific reports 3, 3463 (2013).
FIRST model
RED VERSuS BLUE
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993622/latex_802d0c0383c789c1dac8fa0fc580c7ad.png)
N. F. Johnson, et al., Scientific reports 3, 3463 (2013).
Interevent time between attacks n-1 and n
FIRST model
RED VERSuS BLUE
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993622/latex_802d0c0383c789c1dac8fa0fc580c7ad.png)
N. F. Johnson, et al., Scientific reports 3, 3463 (2013).
Interevent time between attacks n-1 and n
Attack number
FIRST model
RED VERSuS BLUE
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993622/latex_802d0c0383c789c1dac8fa0fc580c7ad.png)
N. F. Johnson, et al., Scientific reports 3, 3463 (2013).
Interevent time between attacks n-1 and n
Escalation rate
Attack number
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993661/m1all.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993622/latex_802d0c0383c789c1dac8fa0fc580c7ad.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993661/m1all.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993670/m1_k12.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993622/latex_802d0c0383c789c1dac8fa0fc580c7ad.png)
College
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993661/m1all.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993669/m1_college.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993670/m1_k12.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993622/latex_802d0c0383c789c1dac8fa0fc580c7ad.png)
College
K12
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993689/lateeary.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993689/lateeary.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993691/earlylatestats.png)
What can we do with this model:
- UNDERSTAND TRENDS, focus efforts on campuses.
- understand WHAT TYPE OF ATTACKS ARE COMING.
SECOND model
HAWKES PROCESS
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993620/latex_cbc4aa455cd71b84469217f6d2400967.png)
D. Marsan, O. Lengliné, Science 319, 1076 (2008).
A. G. Hawkes, D. Oakes, Journal of Applied Probability pp. 493–503 (1974).
SECOND model
HAWKES PROCESS
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993620/latex_cbc4aa455cd71b84469217f6d2400967.png)
D. Marsan, O. Lengliné, Science 319, 1076 (2008).
A. G. Hawkes, D. Oakes, Journal of Applied Probability pp. 493–503 (1974).
Attack rate at space point x and time t
SECOND model
HAWKES PROCESS
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993620/latex_cbc4aa455cd71b84469217f6d2400967.png)
D. Marsan, O. Lengliné, Science 319, 1076 (2008).
A. G. Hawkes, D. Oakes, Journal of Applied Probability pp. 493–503 (1974).
Attack rate at space point x and time t
Base attack rate
SECOND model
HAWKES PROCESS
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/2993620/latex_cbc4aa455cd71b84469217f6d2400967.png)
D. Marsan, O. Lengliné, Science 319, 1076 (2008).
A. G. Hawkes, D. Oakes, Journal of Applied Probability pp. 493–503 (1974).
Attack rate at space point x and time t
Base attack rate
Influence of previous attacks
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/3017456/h4.png)
distance component
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/3017457/h3.png)
time component
What can we do with this model:
- focus efforts on federal prevention programs.
- quantify the time decay.
Conclusions
1. School shootings cluster in time, but not in space (except within-town attacks).
2. School shootings get media attention, which in turn affect the probability of new attacks (copycat effect).
3. We can model the relationship in several ways:
3.1. Blue vs Red model:
- We find distinct trends in school shootings (College vs K12)
- The outliers in the model have distinctive characteristics.
3.2. Hawkes process:
- The attacks are randomly distributed in space (except within-town).
- The attacks increase the probability of new attacks during months.
Conclusions
1. School shootings cluster in time, but not in space (except within-town attacks).
2. School shootings get media attention, which in turn affect the probability of new attacks (copycat effect).
3. We can model the relationship in several ways:
3.1. Blue vs Red model:
- We find distinct trends in school shootings (College vs K12)
- The outliers in the model have distinctive characteristics.
3.2. Hawkes process:
- The attacks are randomly distributed in space (except within-town).
- The attacks increase the probability of new attacks during months.
Conclusions
1. School shootings cluster in time, but not in space (except within-town attacks).
2. School shootings get media attention, which in turn affect the probability of new attacks (copycat effect).
3. We can model the relationship in several ways:
3.1. Blue vs Red model:
- We find distinct trends in school shootings (College vs K12)
- The outliers in the model have distinctive characteristics.
3.2. Hawkes process:
- The attacks are randomly distributed in space (except within-town).
- The attacks increase the probability of new attacks during months.
Conclusions
1. School shootings cluster in time, but not in space (except within-town attacks).
2. School shootings get media attention, which in turn affect the probability of new attacks (copycat effect).
3. We can model the relationship in several ways:
3.1. Blue vs Red model:
- We find distinct trends in school shootings (College vs K12)
- The outliers in the model have distinctive characteristics.
3.2. Hawkes process:
- The attacks are randomly distributed in space (except within-town).
- The attacks increase the probability of new attacks during months.
THANK YOU
1. School shootings cluster in time, but not in space (except within-town attacks).
2. School shootings get media attention, which in turn affect the probability of new attacks (copycat effect).
3. We can model the relationship in several ways:
3.1. Blue vs Red model:
- We find distinct trends in school shootings (College vs K12)
- The outliers in the model have distinctive characteristics.
3.2. Hawkes process:
- The attacks are randomly distributed in space (except within-town).
- The attacks increase the probability of new attacks during months.
http://bit.ly/2d7N3Qr
arxiv: 1506.06305
@uvaCORPNET // @javiergb_com garcia@uva.nl
![](https://s3.amazonaws.com/media-p.slid.es/uploads/137516/images/3017469/d1.png)
CCS_school_shootings
By Javier GB
CCS_school_shootings
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