The language of the internet

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Throughout his academic career, Johannes Eichstaedt has always worked with data – it’s just that initially, as a physicist, it was particle physics data rather than psychological data he was processing. But when he realised that he “didn’t much care for working in a particle accelerator”, Eichstaedt switched to psychology.

Now, as a data scientist in psychology at the University of Pennsylvania, and co-founder of the World Well-Being Project, his time is spent using natural language processing to measure well-being among populations.

His research has included using Tweets to predict heart disease and Facebook statuses to identify depression.

Language patterns

In the case of heart disease and Twitter, he was part of the team of scientists that analysed more than 50, 000 tweeted words to characterise community-level psychological correlates of dying from atherosclerotic heart disease (AHD) in the US.

The language patterns identified as risk factors reflected negative social relationships, disengagement and negative emotions such as ...