In Isaac Asimov’s Foundation series, the future of masses of people can be predicted with “psychohistory,” a method of predicting future political and social trends, using a device called the “Prime Radiant.” In the 1950s, there wasn’t the math or the computational power available to make such a thing reality. Now there might be.
Supercomputers, such as the Nautilus at the University of Tennessee’s Center for Data Analysis and Visualization, may have brought the world closer to Asimov’s vision, though it is still early days. The key is seeking patterns in massive amounts of data and being able to visualize them. Kaley Leetaru, assistant director for text and digital media analytics at the University of Illinois Urbana-Champaign, did just that.
Leetaru used a database of 100 million news articles spanning the period from 1979 to early 2011. The data is from the Open Source Center and Summary of World Broadcasts, both set up by the U.S. and British intelligence agencies to monitor what amounts to nearly every news source in the world, and translate them into nuanced English. By analyzing the text in the news stories and the tone — whether they were largely positive or negative — Leetaru found that patterns emerged that seem to line up with major periods of unrest. For example, in Egypt, the tone of news articles about Mubarak grew increasingly negative as the protests grew, until eventually Mubarak resigned.
It isn’t just the tone, however — it’s also the change in tone over time. Saudi Arabia’s government has remained in power, because the tone of the news there has been equally negative before, whereas Tunisia and Egypt hit new lows. Leetaru notes that many of the country experts on Egypt said Mubarak would likely ride it out, as he had done before.