Twitter Media Being Used to Predict Heart Disease
By Petrina Smith
Thursday, 22 January, 2015
Thursday, 22 January, 2015
Interesting research published in the Journal Psychological Science shows that Twitter can be used to indicate a community's psychological well being and even predict rates of heart disease.
The research, a joint project between the University of Melbourne and the University of Pennsylvania, shows that Twitter not only predicts hear disease risk and other traditional factors, but also acts as a psychological barometer
The researchers found that expressions of negative emotions, such as “hate”, “bored”, and expletives, in local community tweets were associated with higher heart disease risk, even after variables like income and education were taken into account. However, words like “wonderful” and “friends” were associated wInteresting research published in the Journal Psychological Science shows that Twitter can be used to indicate a community's psychological well being and even predict rates of heart disease. ith lower risk.
Lead author Dr Margaret Kern from the Centre for Positive Psychology Graduate School of Education and Johannes Eichstaedt from the University of Pennsylvania said that although researchers assume that the psychological well being of communities is important for physical health, it is hard to measure.
“Using Twitter as a window into a community’s collective mental state may provide a useful tool in epidemiology and for measuring the effectiveness of public-health interventions,” Dr Kern said.
Drawing on a set of public tweets made between 2009 and 2010, the researchers used established emotional expressions as well as automatically generated clusters of words reflecting behaviours and attitudes, to analyse a random sample of tweets from individuals who had made their locations available.
There were enough tweets and health data from about 1300 US counties, containing 88 percent of the country’s population. Coronary heart disease, the leading cause of death worldwide proved an ideal measure.
“We can’t predict the number of heart attacks a community will have in a given timeframe, but the language may reveal places to intervene.”
The team’s findings show that these tweets are aggregating information about people that can’t be readily accessed in other ways.
“We believe that we are picking up more long-term characteristics of communities,” Mr Eichstaedt said.
Dr Kern noted, “The world of social media is a new frontier for social science research.”
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