Friday, November 25, 2016
Still Awaiting Omniscience
"In new research published Thursday in the journal Science, Northeastern network scientist David Lazer and his colleagues analyzed the effectiveness of four global-scale databases and found they are falling short when tested for reliability and validity.
The fully automated systems studied were the International Crisis Early Warning System, or ICEWS, maintained by Lockheed Martin, and Global Data on Events Language and Tone, or GDELT, developed and run out of Georgetown University. The others were the hand-coded Gold Standard Report, or GSR, generated by the nonprofit MITRE Corp., and the Social, Political, and Economic Event Database, or SPEED, at the University of Illinois, which uses both human and automated coding.
"It's so easy for us as humans to read something and know what it means," says Lazer. "That's not so for a set of computational rules."
The authors suggest that reliable data-tracking systems can be used to build models that anticipate the escalation of conflicts, forecast the progression of epidemics, or trace the effect of global warming on the ecosystem."
Using Big Data to monitor societal events shows promise, but the coding tech needs work
phys.org, Oct 2016