Twitter Valuable in Predicting Rates of Coronary Heart Disease
Researchers from the University of Pennsylvania say they have shown that Twitter can serve as a dashboard indicator of a community’s psychological wellbeing as well as predict rates of heart disease.
Researchers from the University of Pennsylvania say they have shown that Twitter can serve as a dashboard indicator of a community's psychological wellbeing as well as predict rates of heart disease.
Their study, published in the journal Psychological Science, found that expressions of negative emotions such as anger, stress and fatigue in a county's tweets were associated with higher heart disease risk. At the same time, positive emotions like excitement and optimism were associated with lower risk.
While previous studies have identified traditional factors that contribute to the risk of heart disease, such as low income or smoking, Penn researchers have demonstrated that Twitter can capture more information about heart disease risk than many traditional factors combined, as the social media platform also characterizes the psychological atmosphere of a community.
"Twitter seems to capture a lot of the same information that you get from health and demographic indicators," said Gregory Park, a postdoctoral fellow in the School of Arts and Science's Department of Psychology, "but it also adds something extra. So predictions from Twitter can actually be more accurate than using a set of traditional variables."
Leveraging a set of public tweets made between 2009 and 2010, researchers used established emotional dictionaries, as well as automatically generated clusters of words reflecting behaviors and attitudes, to analyze a random sample of tweets from individuals who had made their locations available. They found that negative emotional language and topics, such as words like "hate" or expletives, remained strongly correlated with heart disease mortality, even after variables like income and education were taken into account.
On the other hand, positive emotional language showed the opposite correlation, suggesting that optimism and positive experiences, words like "wonderful" or "friends," may be protective against heart disease.
"The relationship between language and mortality is particularly surprising," said H. Andrew Schwartz, a visiting assistant professor in the School of Engineering and Applied Science's Department of Computer and Information Science, "since the people tweeting angry words and topics are in general not the ones dying of heart disease. But that means if many of your neighbors are angry, you are more likely to die of heart disease."
Their study, published in the journal Psychological Science, found that expressions of negative emotions such as anger, stress and fatigue in a county's tweets were associated with higher heart disease risk. At the same time, positive emotions like excitement and optimism were associated with lower risk.
While previous studies have identified traditional factors that contribute to the risk of heart disease, such as low income or smoking, Penn researchers have demonstrated that Twitter can capture more information about heart disease risk than many traditional factors combined, as the social media platform also characterizes the psychological atmosphere of a community.
"Twitter seems to capture a lot of the same information that you get from health and demographic indicators," said Gregory Park, a postdoctoral fellow in the School of Arts and Science's Department of Psychology, "but it also adds something extra. So predictions from Twitter can actually be more accurate than using a set of traditional variables."
Leveraging a set of public tweets made between 2009 and 2010, researchers used established emotional dictionaries, as well as automatically generated clusters of words reflecting behaviors and attitudes, to analyze a random sample of tweets from individuals who had made their locations available. They found that negative emotional language and topics, such as words like "hate" or expletives, remained strongly correlated with heart disease mortality, even after variables like income and education were taken into account.
On the other hand, positive emotional language showed the opposite correlation, suggesting that optimism and positive experiences, words like "wonderful" or "friends," may be protective against heart disease.
"The relationship between language and mortality is particularly surprising," said H. Andrew Schwartz, a visiting assistant professor in the School of Engineering and Applied Science's Department of Computer and Information Science, "since the people tweeting angry words and topics are in general not the ones dying of heart disease. But that means if many of your neighbors are angry, you are more likely to die of heart disease."
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