By guest blogger Jon Brock
Johannes Eichstaedt was sitting in a coffee shop by Lake Atitlan in Guatemala when he received a slack about a tweet about a preprint. In 2015, the University of Pennsylvania psychologist and his colleagues published a headline-grabbing article linking heart disease to the language used on Twitter. They’d found that tweets emanating from US counties with high rates of heart disease mortality tended to exhibit high levels of negative emotions such as anger, anxiety, disengagement, aggression, and hate. The study, published in Psychological Science, has proven influential, already accruing over 170 citations. But three years later, the preprint authors Nick Brown and James Coyne from the University of Groningen claimed to have identified “numerous conceptual and methodological limitations”. Within the month, Eichstaedt and his colleagues issued a riposte, publishing their own preprint that claims further evidence to support their original conclusions.
As recent revelations surrounding Facebook and Cambridge Analytica have highlighted, corporations and political organisations attach a high value to social media data. But, Eichstaedt argues, that same data also offers rich insights into psychological health and well-being. With appropriate ethical oversight, social media analytics could promote population health and perhaps even save lives. That at least is its promise. But with big data come new challenges – as Eichstaedt’s “debate” with Brown and Coyne illustrates.
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