Researchers analyse tweets to predict whether users are getting sick
- From: news.com.au
- February 11, 2013
- Researchers analyse Twitter to predict illness
- Data includes GPS data, content and activity
- Develop app Germ Tracker which maps illness
WHAT if instead of going to the doctor, you could find out whether you're sick based on your tweets?
This is what a group of researchers from the US have tried to investigate.
Scientists from the University of Rochester found that Twitter could be used to predict how likely users were to become sick.
They analysed thousands of tweets - looking at things such as proximity to sources of pollution, the amount of time users caught public transport, went to the gym or visited restaurants - and found that pretty much any activity involving human contact "significantly increased health risks".
No real surprise there.
While people who regularly went to the gym were marginally more likely to get sick than less active individuals, the researchers found that people who tweet about going to the gym but never actually go get sick "significantly more often".
The researchers used GPS information as well as the content of tweets to verify the findings.
And this isn't just some abstract concept either - the scientists have developed a web app - called Germ Tracker - that allows users to track health risks based on GPS and Twitter content.
"This app can be used by people to make personal decisions about their health," lead researcher Adam Sadilek said.
"For example, they might want to avoid a subway station if it's full of sick people.
"It could also be used in conjunction with other methods by governments or local authorities to try to understand outbursts of the flu."
The app uses machine-learning so the more information is entered into it, the better it will get at predicting whether a Twitter user is sick.
"It's like teaching a baby a new language," Mr Sadilek said.
"We need the algorithm to understand that someone who tweets 'I'm sick and have been in bed all day' should be characterised as sick, but 'I'm sick of driving around in this traffic' shouldn't be."
The app also allows users to source the specific tweet that led the algorithm to classify them as sick, not sick, high risk or low risk.
It also lets you assess whether you agree with the classification.
At present the app is only available for online, rather than as a smartphone app. So you might want to get into the habit of checking GermTracker before leaving the house in the morning. The app is also available on mobile but you will have to use your web browser of choice.