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Supercomputers being used to predict revolutions

September 21, 2011 By: Dr Search Principal Consultant at the Search Clinic Category: Computers, Technology Companies, Uncategorized

Inputting new stories into a supercomputer may help predict major world events according to US research.Supercomputers being used to predict revolutionsA study, based on millions of articles, charted deteriorating national sentiment ahead of the recent revolutions in Libya and Egypt.

While the analysis was carried out retrospectively, scientists say the same processes could be used to anticipate upcoming conflict.

The system also picked up early clues about Osama Bin Laden’s location.

Kalev Leetaru, from the University of Illinois’ Institute for Computing in the Humanities, Arts and Social Science, presented his findings in the journal First Monday.

The study’s information was taken from a range of sources including the US government-run Open Source Centre and BBC Monitoring, both of which monitor local media output around the world.

News outlets which published online versions were also analysed, as was the New York Times’ archive, going back to 1945.

In total, Mr Leetaru gathered more than 100 million articles.

Reports were analysed for two main types of information: mood – whether the article represented good news or bad news, and location – where events were happening and the location of other participants in the story.

Mood detection, or “automated sentiment mining” searched for words such as “terrible”, “horrific” or “nice”.

Location, or “geocoding” took mentions of specific places, such as “Cairo” and converted them in to coordinates that could be plotted on a map.

Analysis of story elements was used to create an interconnected web of 100 trillion relationships.

Data was fed into an SGI Altix supercomputer, known as Nautilus, based at the University of Tennessee.

The machine’s 1024 Intel Nehalem cores have a total processing power of 8.2 teraflops (trillion floating point operations per second).

Based on specific queries, Nautilus generated graphs for different countries which experienced the “Arab Spring”.

In each case, the aggregated results of thousands of news stories showed a notable dip in sentiment ahead of time – both inside the country, and as reported from outside.

Egypt sentiment graph Media “sentiment” around Egypt fell dramatically in early 2011, just before the resignation of President Mubarak.

For Egypt, the tone of media coverage in the month before President Hosni Mubarak’s resignation had fallen to a low only seen twice before in the preceding 30 years.

Previous dips coincided with the 1991 US aerial bombardment of Iraqi troops in Kuwait and the 2003 US invasion of Iraq.

Similar drops were seen ahead of the revolution in Libya and the Balkans conflicts of the 1990s.

Saudi Arabia, which has thus far resisted a popular uprising, had experienced fluctuations, but not to the same extent as some other states where leaders were eventually overthrown.

The computer event analysis model appears to give forewarning of major events, based on deteriorating sentiment.

However, in the case of this study, its analysis is applied to things that have already happened. According to Kalev Leetaru, such a system could easily be adapted to work in real time, giving an element of foresight.

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