Predicting the Future: Women and the Anti-Terror Algorithm

On 9 September 2016, the Guardian reported: Cell of French women guided by Isis behind failed Notre Dame attack, indicating that ISIS-supporting female jihadis targeted one of the French cathedrals associated with the feminine heart of Christianity. Image Source: Guardian.

On 16 June 2016, the New York Times reported that a physicist at the University of Miami is developing an algorithm to analyze social media communications in order to predict terrorist attacks:

"After Orlando and San Bernardino and Paris, there is new urgency to understand the signs that can precede acts of terrorism. And with the Islamic State’s prolific use of social media, terrorism experts and government agencies continually search for clues in posts and Twitter messages that appear to promote the militants’ cause.

A physicist may not seem like an obvious person to study such activity. But for months, Neil Johnson, a physicist at the University of Miami, led a team that created a mathematical model to sift order from the chaotic pro-terrorism online universe.

In a study published Thursday in the journal Science, Dr. Johnson and Miami colleagues searched for pro-Islamic State posts each day from mid-2014 until August 2015, mining mentions of beheadings and blood baths in multiple languages on Vkontakte, a Russia-based social media service that is the largest European equivalent to Facebook. Ultimately, they devised an equation that tries to explain the activity of Islamic State sympathizers online and might, they say, eventually help predict attacks that are about to happen."

Johnson describes his research as follows:

"My research looks at the physics of collective behavior and emergent properties in real-world systems which are 'complex': from the physical, biological, medical domains through to social and even financial domains. A complex system is one in which unexpected phenomena emerge spontaneously at the macro-level, through the micro-level interactions of many objects over time. For example, traffic jams arise from the interactions of cars -- but understanding what a single car can do tells us little about the jams that emerge. The same holds true for applications in medicine (cancer tumors), molecular biology (macroscopic chromosone dynamics within E. Coli), neurology (brain function from individual neuron firings) through to economics and sociology (mass downloads of a given YouTube video, or crashes in financial markets). The fascinating feature of Complex Systems is that they all contain many interacting objects, with strong feedback from both inside and outside the system, and are typically far from equilibrium and exhibit extreme behavior."

Dr. Johnson's Website is here and another report on his studies of 200 ISIS online communities is here. He found that women users cemented ISIS online communal terror initiatives, potentially in part because of their strong communications and social abilities, combined with the fact that they are shut out of positions of communal authority in conventional systems of organization:

"We were surprised to find that 40% of followers declared themselves to be female. Women hold an unexpected position in the pro-ISIS networks — they tend to be centres of information-flow between followers, and to increase the lifespan of the communities. They typically do not have similarly prominent roles in comparable networks from the everyday world, such as innovation networks for patents in industry and academia."

See further reports on Johnson's work on chaos and predictability in war (here) and a formula for threats (here):

"Using the lens of complexity science, our research team based at the University of Miami have recently shown that the SAME statistical pattern lies hidden in these nightly casualty figures across a wide range of insurgent conflicts and terrorist campaigns -- from the deserts in Iraq, to the jungles in Colombia, and from the streets of Northern Ireland to the mountains of Afghanistan and Pakistan. The implication is that the WAY in which insurgents and terrorists carry out day-to-day violent attacks is statistically the same everywhere -- irrespective of where they are or why they are doing it. And just as medical diagnostics can help specialists treat new diseases as they arise, so our findings offer new insight into how insurgent and terrorist groups organize themselves and hence how best to disrupt them."

The article on the anti-terror algorithm was published in Science on 17 June 2016, New online ecology of adversarial aggregates: ISIS and beyond (Science 17 Jun 2016: Vol. 352, Issue 6292, pp. 1459-1463 DOI: 10.1126/science.aaf0675).