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听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 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 鈥渉ate鈥�, 鈥渂ored鈥�, 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 鈥渨onderful鈥� and 鈥渇riends鈥� 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.
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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.听
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鈥淯sing Twitter as a window into a community鈥檚 collective mental state may provide a useful tool in epidemiology and for measuring the effectiveness of public-health interventions,鈥� Dr Kern said.
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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.听
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There were enough tweets and health data from about 1300 US counties, containing 88 percent of the country鈥檚 population. Coronary heart disease, the leading cause of death worldwide proved an ideal measure. 听
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鈥淲e can鈥檛 predict the number of heart attacks a community will have in a given timeframe, but the language may reveal places to intervene.鈥�
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The team鈥檚 findings show that these tweets are aggregating information about people that can鈥檛 be readily accessed in other ways.听
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鈥淲e believe that we are picking up more long-term characteristics of communities,鈥� Mr Eichstaedt said.
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Dr Kern noted, 鈥淭he world of social media is a new frontier for social science research.鈥�
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