Re: Pricing a Protest: Forecasting the Dynamics of Civil

[walter palmetshofer]

Maybe this is interesting in that context:

Social Unrest: Millennial Uprising Scenario 2015 by Cambridge Centre for Risk 
Studies

slides 
http://www.risk.jbs.cam.ac.uk/news/events/other/downloads/150122_riskbriefing_socialunrestrisk_slides.pdf

report http://cambridgeriskframework.com/getdocument/22

Also a few days ago there was the Recorded Future User Network
Conference, perhaps Dan Geer can chip in on the latest.

>From the department nothing new under the sun:

This was from 2012 

http://semanticommunity.info/AOL_Government/2012_Recorded_Future_User_Conference

back then recordedfuture had interesting webinars on monitoring protest 
and social unrest, here claiming 85% accuracy for their prediction 2012 

https://youtu.be/ffPSocrmfQI?t=213

Monitoring Protests and Unrest - Recorded Future Webcast 2012

https://www.youtube.com/watch?v=6Sbny91NjeA

Monitoring Social Media Authors 2014

https://www.youtube.com/watch?v=BGMg1jNF3D4

also interesting Quid https://youtu.be/mKZCa_ejbfg?t=890

CEO 

https://gigaom.com/2013/05/21/the-future-of-propaganda-a-qa-with-sean-gourley-about-big-data-and-the-war-of-ideas/

http://www.npr.org/sections/alltechconsidered/2012/05/14/152444019/algorithms-the-ever-growing-all-knowing-way-of-the-future

and the above mentioned Cytora - Real-Time Political Risk Analysis 

https://www.youtube.com/watch?v=gJsriO_o_9I

Future research projects http://minerva.dtic.mil/funded.html

And then there is always enterprise solution Palantir.


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Pricing a Protest: Forecasting the Dynamics of Civil Unrest Activity

[nettime's dual-use researcher]

http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0139911

Abstract

Online social media activity can often be a precursor to disruptive
events such as protests, strikes, and “occupy” movements. We have
observed that such civil unrest can galvanize supporters through
social networks and help recruit activists to their cause.
Understanding the dynamics of social network cascades and
extrapolating their future growth will enable an analyst to detect or
forecast major societal events. Existing work has primarily used
structural and temporal properties of cascades to predict their future
behavior. But factors like societal pressure, alignment of individual
interests with broader causes, and perception of expected benefits
also affect protest participation in social media. Here we develop an
analysis framework using a differential game theoretic approach to
characterize the cost of participating in a cascade, and demonstrate
how we can combine such cost features with classical properties to
forecast the future behavior of cascades. Using data from Twitter, we
illustrate the effectiveness of our models on the “Brazilian Spring”
and Venezuelan protests that occurred in June 2013 and November 2013,
respectively. We demonstrate how our framework captures both
qualitative and quantitative aspects of how these uprisings manifest
through the lens of tweet volume on Twitter social media.

Citation: Goode BJ, Krishnan S, Roan M, Ramakrishnan N (2015) Pricing
a Protest: Forecasting the Dynamics of Civil Unrest Activity in Social
Media. PLoS ONE 10(10): e0139911. doi:10.1371/journal.pone.0139911

Funding: This work was supported by the Intelligence Advanced Research
Projects Activity (IARPA)







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