AI Article Synopsis
- Twitter can be used to quickly collect information about illnesses because people often share their symptoms there.
- Researchers created a simple computer program to find everyday words related to medical terms to better understand what people are saying about their symptoms.
- They used this information to track tweets about flu symptoms and found that their results matched well with official health data in the U.S.
Article Abstract
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 algorithm that exploits the abundance of health-related web pages to identify all jargon expressions related to a specific technical term. We then translated an influenza case definition into a Boolean query, each symptom being described by a technical term and all related jargon expressions, as identified by the algorithm. Subsequently, we monitored all tweets that reported a combination of symptoms satisfying the case definition query. In order to geolocalize messages, we defined 3 localization strategies based on codes associated with each tweet. We found a high correlation coefficient between the trend of our influenza-positive tweets and ILI trends identified by US traditional surveillance systems.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3853203 | PMC |
| http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0082489 | PLOS |
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