A new study shows interest in how to use social media to predict civil unrest or crimes.
It should come as no surprise that people want to use social media to determine what is going to happen in the future so they can control it. Never before have millions of people put their thoughts and feelings in a publicly accessible forum that is easily searchable. Of course, much of the interest comes from companies wanting to use social media to increase their revenue. But some of the uses are undeniably political in nature.
A team from the Pacific Northwest National Laboratory and the University of Washington have collated the results of hundreds of separate studies and found that social media can “make predictions about the future” – although these forecasts are not always accurate.
Twitter analysis can accurately predict civil unrest, for instance, because people use certain hashtags to discuss issues online before their anger bubbles over into the real world.
The most famous example of this came during the Arab Spring, when clear signs of the impending protests and unrest were found on social networks days before people took to the streets.
A system called EMBERS (Early Model Based Event Recognition using Surrogates) has also yielded “impressive results” not just in “detecting events, but in detecting specific properties of those events”.
It has been used to predict unrest in South America, forecasting events with 80 per cent accuracy in Brazil and a slightly underwhelming 50 per cent in Venezuela.
Another study showed “impressive” results in detecting “civil unrest” linked to the Black Lives Matter group, which formed in America in response to police shootings.
Social media offers “some value” to police looking to predict future crimes, the researchers continued.
Cops could combine historical data about where and when crimes were committed with social media posts to have a stab at working out the likelihood of offences occurring at certain places and times.
“Of the 25 crime types examined, 19 see a forecasting improvement by incorporating SM data,” the academics added.
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