Psychologists are discovering just how much information about our inner states can be gleaned from social media.
For some people, posting to social media is as automatic as breathing. At lunchtime, you might pop off about the latest salad offering at your local lettucery. Or, late that night, you might tweet, “I can’t sleep, so I think I’m just going to have a glass of wine” without a second thought.
DOES THE END REALLY JUSTIFY THE MEANS IN ALL CASES
Over time, all these Facebook posts, Instagram captions, and tweets have become a treasure trove of human thought and feeling. People might rarely look back on their dashed-off online thoughts, but if their posts are publicly accessible, they’re ripe for analysis. And some psychologists are using algorithms to figure out what exactly it is we mean by these supposedly off-the-cuff pronouncements.
According to new research, for instance, a tweet like “I’m up at 2 a.m. drinking wine by myself” says one thing pretty clearly: “I’m lonely.” For a study in BMJ Open, researchers at the University of Pennsylvania analyzed 400 million tweets posted by people in Pennsylvania from 2012 to 2016. The authors scraped together the Twitter posts of users whose tweets contained at least five mentions of the words lonely or alone, and compared them with a control group with similar demographics. (The authors did not explicitly ask those who often tweeted about loneliness whether they actually were lonely.)
The seemingly lonely people swore more, and talked more about their relationship problems and their needs and feelings. They were more likely to express anxiety or anger, and to refer to drugs and alcohol. They complained of difficulty sleeping and often posted at night. The non-lonely control group, perhaps fittingly, began a lot more conversations by mentioning another person’s username. They also posted more about sports games, teams, and things being “awesome.”
This study was far from a perfect window into Twitter users’ souls. Certainly, people can talk about their needs and feelings without being lonely. But natural-language processing is nevertheless making it easier for scientists to understand what different emotions look like online. In recent years, researchers have used social-media data to predict which users are depressed and which are especially happy. As the tools for analysis become more sophisticated, a wide array of emotions and mental-health conditions can now be predicted using the words that people are already typing into their phones and computers every day.
In some cases, researchers can unearth fine-grained differences within amorphous emotions. Take, for instance, empathy. There’s long been an idea in psychology that there are two types of empathy: “Beneficial” empathy, or compassion, involves sympathizing with someone and trying to help that person. Meanwhile, “depleting” empathy entails feeling someone’s actual pain—and suffering yourself in the process. For a paper that is still undergoing peer review, another group of researchers at the University of Pennsylvania analyzed social-media language to determine how these two types of empathy are expressed. They found that people who demonstrate compassion tend to say things like “blessed,” “wonderful,” “prayers,” or “family.” Those who express depleting empathy use words like “me,” “feel,” “myself,” and “anymore.”
This might seem like a minor distinction, but according to Lyle Ungar, one of the study’s authors, finding the difference between the two can help people in jobs that involve caring for others, such as doctors, understand when their empathy might be counter-productive. Depleting empathy can lead to burnout. “I can really care about you and not suffer with you,” Ungar says. “I can worry that there’s poverty in Africa and donate money to charity without feeling what it’s like to have malaria.”
Beyond common emotions, language-analysis technology might also shed light on more serious conditions. It might one day be used to predict psychosis in patients with bipolar disorder or schizophrenia. Episodes of psychosis, or losing touch with reality, can be shortened or even stopped if caught early enough, but many patients are too far gone by the time loved ones realize what’s happening. And it’s difficult for people going through psychosis to realize they’re in the midst of it.
Last month, researchers from Northwell Health and the Georgia Institute of Technology analyzed 52,815 Facebook posts from 51 patients who had recently experienced psychosis. They found that the language the patients used on Facebook was significantly different in the month preceding their psychotic relapse, compared with when they were healthy. As their symptoms grew worse, they were more likely to swear, or to use words related to anger or death, and they were less likely to use words associated with work, friends, or health. They also used first-person pronouns, a possible sign of what’s called “self-referential thinking,” the study authors write, or the tendency for people who are experiencing delusions to falsely think that strangers are talking about them. (In the recent loneliness study, the lonely Twitter users were also more likely to use the words myself or I than the control group.)
Those experiencing psychosis more frequently “friended” and tagged others on Facebook in the month before their relapse. It’s not so much that making new friends on Facebook is problematic, says Michael Birnbaum, an assistant behavior-science professor at Northwell Health and lead author on the study. It’s that the increased activity reflects a shift in behavior in general—which could be a sign of an upcoming psychotic break. “It’s something that they wouldn’t typically do when they were in a period of relative health,” Birnbaum says.