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[liberationtech] Computer analysis predicted rises, ebbs in Afghanistan violence

Yosem Companys companys at stanford.edu
Fri Jul 20 12:56:21 PDT 2012


latimes.com/news/science/la-sci-warfare-data-20120717,0,409336.story
latimes.comComputer analysis predicted rises, ebbs in Afghanistan
violence Researchers
used previous data of violence in Afghanistan to predict with striking
accuracy which areas of the country in 2010 would see more bloodshed and
which would see less.

By Jon Bardin, Los Angeles Times

July 17, 2012

In August 2010, shortly after WikiLeaks released tens of thousands of
classified documents that cataloged the harsh realities of the war in
Afghanistan, a group of friends — all computer experts — gathered at the
New York City headquarters of the Internet company Bitly Inc. to try and
make sense of the data.

The programmers used simple code to extract dates and locations from about
77,000 incident reports that detailed everything from simple
stop-and-search operations to full-fledged battles. The resulting map
revealed the outlines of the country's ongoing violence: hot spots near the
Pakistani border but not near the Iranian border, and extensive bloodshed
along the country's main highway. They did it all in just one night.

Now one member of that group has teamed up with mathematicians and computer
scientists and taken the project one major step further: They have used the
WikiLeaks data to predict the future.

Based solely on written reports of violence from 2004 to 2009, the
researchers built a model that was able to foresee which provinces would
experience more violence in 2010 and which would have less. They could also
anticipate how much the level of violence went up or down.

The project, whose results were published online Monday by the Proceedings
of the National Academy of Sciences, is part of a growing movement to
understand and predict episodes of political and military conflict using
automated computational techniques.

The availability of huge amounts of data combined with steady increases in
computing power has prompted experts to bring the rigor of objective
quantitative analysis to realms that were once considered fundamentally
subjective, including literature and the study of social groups.

"For the first time, we have large data sets from places like Facebook and
Twitter that we can analyze with high-powered computers and get meaningful
results," said Paulo Shakarian, a computer scientist at the United States
Military Academy at West Point, who is working on an algorithm to predict
the location of insurgent weapons caches. "Iraq and Afghanistan are the
very first conflicts where we have been collecting as much data as we
possibly can."

In the case of the WikiLeaks data, the researchers sought to find a general
pattern to the violence in Afghanistan and use it to predict how violence
would change in each province in 2010 — the year President Obama increased
the number of U.S. troops in the country.

"The model we employed is both complex and simple," said Guido Sanguinetti,
an expert in computational sciences at the University of Edinburgh in
Scotland and the study's senior author. "It doesn't take in any knowledge
of military operations or political events, and it treats all types of
violence exactly the same, whether it's a stop-and-search or a big battle."

Even with these ostensibly key details missing, the researchers found that
they could predict 2010's events with striking accuracy.

And the model wasn't tripped up by Obama's decision to send 30,000
additional troops, which introduced a new dimension to the Afghanistan
conflict.

"Our findings seem to prove that the insurgency is self-sustaining,"
Sanguinetti said. "You may throw a large military offensive, but this
doesn't seem to disturb the system."

The study authors said they were most surprised that the model could
predict activity even in Afghanistan's relatively quiet northern provinces,
where there were fewer data points available to analyze.

"This shows that the escalation we see isn't just attributed to the noise
in the data," said study leader Andrew Zammit Mangion, a computational
sciences researcher at the University of Edinburgh. Instead, he said,
patterns existed nearly everywhere.

Michael Ward, a political scientist at Duke University who has shown that
location data can improve predictions of conflicts, said the study pointed
the way to future research.

"Suppose you could say, 'This is the effect on violence if you build
different types of infrastructure,' " he said. "They don't do that, but
they've set up the framework to do it."

The study also shows why it's important to make as much data public as
possible, Ward said. Without WikiLeaks, he said, a study like this would
have been far more difficult to carry out.

Clionadh Raleigh of Trinity College Dublin, who uses data to predict
violence in Africa based on factors such as the outcomes of local
elections, said the Afghanistan model could be made even better by
including variables such as the political party in power.

"Violence, in general, is a really good predictor of future violence," she
said. But even better would be "to figure out what stops the cycle of
conflict."

Quantitative rigor is making its way into some surprising fields of study.
In 2010, just a few months after the WikiLeaks data dump, Google released a
database of every single word contained in thousands of books published
between 1800 and 2000 — about 4% of all books ever printed. That has
enabled some intrepid researchers to close in on the final frontier:
Studying literature with advanced math.

In a study published last year in Science, experts from Harvard University
and Google were able to detect evidence of censorship regarding
controversial historical figures and events, such as early Soviet official
and Stalin foe Leon Trotsky and the 1989 Tiananmen Square massacre in China.

"That's what this digital humanities focus is being driven toward:
uncovering trends in data that have just never been available before,"
Raleigh said.

*jon.bardin at latimes.com<https://mail.google.com/mail/?view=cm&fs=1&tf=1&to=jon.bardin@latimes.com>
*

Copyright © 2012, Los Angeles Times <http://www.latimes.com/>
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