With our online and real lives increasingly intertwined, scientists and medics must consider digital data in their analysis and research
Psychologists cannot afford to ignore the valuable digital trail of data we leave in our wake
The cursor blinks rhythmically, attempting to attract my attention. My mind, however, is elsewhere. The laptop screen has become a window looking out onto a great digital vastness. This neverending cyber universe, like its physical counterpart, is expanding with incredible velocity.
According to Domo, specialists in business intelligence and data visualisation, we presently upload 300 hours of video to YouTube every minute and send about 15 million text messages every second. Industry pundits also forecast that by 2020 we will have amassed 44 zettabytes – or sextillions – of data. For non-geek speakers, a zettabyte is one billion terabytes, and a terabyte equates to around 1.5 million of those 3.5-inch floppy disks we used to use – remember them? This exponential data growth, with its stupefying numbers and made-up-words, is known as big data, a valuable by-product of our information age.
I see the information age as the birth of an alternate universe. Many of us now live alternate lives, one taking place online and the other in the old world; that messy place where spirit meets bone. The old world is biological, the new one digital and these two worlds are increasingly intertwined.
Psychology prides itself on knitting together the biological, cognitive and social aspects of human experience, which we call the biopsychosocial approach. However, our increasing tendency to live our lives online and in the digital space constitute a whole new dimension to understanding and exploring human behaviour. Perhaps psychology now needs to develop a digital version of the biopsychosocial model.
Psychologists, myself included, have begun to consider the digital world in our analysis and programmes of research. Sure, we can still assess your psychological health by measuring stress hormones or administering questionnaires but your browser history and social media posts can probably tell us just as much, if not more, about your current state.
When you tell someone that you’re a psychologist, there is often a cliched response, which typically involves the person acting defensively and jokingly saying something along the lines of: “Do you know what I’m thinking? Can you read my mind?”. Of course, psychologists don’t know our thoughts or desires, but Google does.
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Google searches – of which we presently make 3.6 million per minute – speak of our desires, interests and needs. A data scientist with access to your online life might be better placed to make predictions about what’s on your mind than a psychologist. Increasingly though, these disciplines – data science and psychology – are collaborating and merging.
For example, a recent study by a team at the University of Pennsylvania and Stony Brook University in New York used Facebook data to identify users with an existing diagnosis of depression. The study, published in Proceedings of the National Academy of Sciences this year, used what the authors describe as "depression-associated language markers". These include things like being highly self-referential – using "I" and "me" a lot – and frequently mentioning feelings of hostility and loneliness in status updates.
This algorithm was sensitive enough to predict a case of depression three months ahead of the condition actually being documented in medical records. This opens up the possibility of using social media data as a method of early detection and relapse prevention in the context of mood disorders.
In a separate study, this time using Google search engine data, researchers were able to monitor the spread of an influenza pandemic across the US. Monitoring health-seeking behaviour in the form of Google search queries significantly outperformed traditional, old world methods of monitoring the spread of sickness. Traditional illness surveillance systems, including those used by the Centers for Disease Control and Prevention in the US, typically have a reporting lag of up to a fortnight; using the Google data cut the delay to just one day.
Medics and psychologists can no longer afford to ignore the fact that much of our lives are conducted online and we leave behind a valuable data trail. For scientists interested in the wellbeing of humanity, this data is invaluable.
Our own psychology research group at Zayed University recently began collaborations with data scientists. Looking at UAE-generated Twitter data from 2016, totalling 140 million tweets, we were able to examine a wide range of questions, from identifying noise annoyance sources and hotspots across the country, to exploring the relationship between sleep patterns and mood. We found people who post most of their tweets between midnight and 5am tended to be the least happy.
In the old world, we used to look to the stars for answers about human behaviour. In the new world, we need to scrutinise big data.
Dr Justin Thomas is professor of psychology at Zayed University