Project
Might Predict Serious Conflicts, Wars Weeks in Advance
Suppose you could accurately predict serious militarized
international conflict weeks, or even months, in advance, potentially
impacting foreign policy?
That’s just what two researchers at Rice hope to do in an unusual collaboration
that mixes political science with computer science.
For several years, Rice computer scientist Devika Subramanian and political scientist
Richard Stoll have worked together using ideas, data, and theories from both
their disciplines to address this problem. Their research project utilizes the
most recent advances in computing facilities, including a supercomputer that
can perform a trillion calculations per second, and takes advantage of the vast
expansion of computer networking to compile information about political events
in various countries over a lengthy period of time.
“We want both to develop new techniques and to adapt existing ones to create
the extensive sets of data about events between countries and to apply models
of international conflict to predict the outbreak of military action,” says
Stoll. The proliferation of news in electronic form has made such an ambitious
goal possible, he says, citing worldwide news sources that can be accessed online,
such as Reuters, Associated Press, United Press International, cnn.com, and the
New York Times. Advances in technologies that can rapidly search these databases
on the Internet and mine them for the relevant information also have made the
study feasible.
The researchers at Rice plan to develop computer programs that gather large sets
of current and archived electronic information sources. They then will use techniques
that already are available to extract data about events between countries. Event
data consists of an action such as a military strike or threat, the country that
initiated the action, the country that was the target, and the date of occurrence.
The actions are scored on a scale that indicates how cooperative or hostile the
country was that initiated the action. The extracted information will be coded
so that it can be analyzed in a variety of fashions, employing techniques from
both computer science and political science.
Subramanian will apply and extend existing algorithms for machine learning and
signal processing to analyze the event data and search for patterns that would
predict the outbreak of serious conflict. One of the key issues is how to aggregate,
or group, the data so it can be analyzed effectively. The researchers want to
develop new conflict-prediction techniques that correlate event data streams
across time and geographic regions. They also want to develop models that can
track the evolution of conflict over time.
“We seek to predict, with a lead time of four to eight weeks, the outbreak
of serious conflicts, even though they might not reach the level of war,” Stoll
says. Analyzing why the conflict occurred will help the researchers develop models
for predicting conflict.
The researchers are well aware that event data sets can become quite large. They
estimate that a global data set spanning the time period of the Cold War is likely
to encompass some 200 million events.
Because of the large volume of data required for this project, the researchers
will take advantage of the Rice Terascale Cluster, a supercomputer being built
at Rice with funding from the National Science Foundation and Intel Corporation,
who also are funding the conflict project. This supercomputer should be able
to perform one trillion calculations per second when it becomes operational next
year.
For preliminary results, Stoll and Subramanian are studying event data from 1979
to 2001 on eight countries in the Middle East. “We know where and when
the serious conflicts occurred, so we can get a reality check on our predictions,” Stoll
says. Using a signal-processing technique called wavelet analysis, they have
discovered discontinuities termed “singularities” in the event data
that are associated with the outbreak of serious conflict.
If the project is successful, it could prove useful to policy-makers. Theoretically,
the information could be made available online, where officials could consult
it and possibly intervene to avoid conflict. “Access to aggregated event
data over a long period of time can have a major impact on policy-making by providing
an additional source of information on which to base foreign-policy decisions,” Stoll
says.
“But first we have to address the core scientific question,” he notes. “How
well can an objective, data-driven approach to modeling the genesis and evolution
of conflict in various regions of the world work?”
The database of event information will be made available to the research community.
—B. J. Almond
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