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June 18th, 2016 
Awake Goy
Susanne Posel ,Chief Editor Occupy Corporatism | Media Spokesperson, HEALTH MAX Group
In the war on terrorism, one thing has become clear since the Orlando shooting – a better way of predicting the radicalization of lone wolves online must be found.
A new research paper suggests that intelligence agencies can learn to tell if the conditions are right for an attack, much like “a doctor who can tell that the conditions are right in a patient for heart disease, while not necessarily predicting exactly when a heart attack will strike.”
Neil Johnson, physicist for the University of Miami, has published a study that demonstrates the unique roll algorithms can play in becoming more proactive about pro-terrorism in social media and other places on the Web.
With funding from the Intelligence Advanced Research Projects Agency (IARPA), a branch of the Office of the National Director of Intelligence (NDI), Johnson’s team collected terroristic subject matter and utilized mathematical models to decipher ISIS threats.
That data stretched back to 2014 to present, singling out terrorism with relation to online activity and civil protests.
Johnson’s team discovered a pattern with “self-organized online groupings, or aggregates, that consist of an ad hoc group of followers of an online page” by using social media data from Facebook and VKontake.
Historically, VKontake is not as quick to shutdown terroristic or hate speech as Facebook which lend to more of those types of people on that network; however in the end, “they uncovered 196 pro-ISIS aggregates involving 108,086 followers between January 1 and August 31, 2015.”
This meant that pro-ISIS networks online proved to be fueled by self-organization in much the same way as is seen in nature; such as schools of fish. Johnson explained that he was reminded of “swarms [or] flocks”.
The team suggested: “Smaller groups will tend to congeal into one big aggregate, which could become far more potent. Instead of people splitting into 196 different groups, there would simply one big group, with 108,000 people across the world all talking the same thing, having the same information, sharing the same everything.”
The lessons gleaned from this research could easily be implemented into federal or state law enforcement agencies:
• Breaking up small pro-terrorist groups can prevent coalescence and stronger networks
• Counterterrorism agencies should pay more attention to groups which “typically” have “only a few hundred” members
Combating the lone wolf issue becomes easier, according to Johnson, because that person “will only truly be alone for short periods of time”. In other words, the “online lone wolf actor” is either in a state of observable online activity or engaging in terroristic activity.
Because the lone wolf “carries the knowledge of pervious [terrorists]”, this research suggests that “there is no such thing as a lone wolf” mathematically speaking.
This is where the spreading of an idea online can be virtually impossible to stop; let alone predict.
Johnson said: “I believe that our machinery could be used to build a timeline of this, or any, lone wolf as they move through these aggregates — and hence what information and influence and motives/plans they are carrying, and hence what threat they are — or how they ended up being the threat that they were.”
It is obvious that shutting down terrorist speech online does not stop its spread because those purveying it are cunning reforming and putting their materials back online.
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