Influenza-Like Illness Surveillance on Twitter through Automated Learning of Naïve Language
Twitter has the potential to be a timely and cost-effective source of data for syndromic surveillance. When speaking of an illness, Twitter users often report a combination of symptoms, rather than a suspected or final diagnosis, using naïve, everyday language. We developed a minimally trained algor...
| Main Authors: | , , , , , , |
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| Format: | Online |
| Language: | English |
| Published: |
Public Library of Science
2013
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3853203/ |