1. What was the "aha" moment where you decided that behavior prediction technology was the path you would dedicate yourself to? Was there something you read or witnessed or experienced?
To clarify — I’m answering your question about my interest in behavior “prediction” technology, but my general interest in psychology and technologies came before this when I was at Stanford and working at NASA)
It was actually a multi-year 'aha' moment. I think all of my ‘aha’ moments come from my interest in doing things that most people think is crazy, weird, or not possible. If my pursuit leads to something valuable, it sparks an ‘aha’ moment. For example, my friend Gopal was working at Cisco and pulled me to work with him on a project called "mind map, or using technologies to map how humans think.
It was an ambitious project and so we started small looking at whether we could use data to predict anything about people. This was back in 2006 or 2007 when Facebook was growing and we could use Facebook book data for the study. I started keeping spreadsheets of my friends on Facebook to learn when they changed their profiles and explore why. I would document, by hand, when they changed anything, like when they added where they were going to school, removed an interest in football from their profile and replaced it by saying were interested in baseball instead, or changed their relationship status from single to "it's complicated." I'd call up my friends and ask them why they changed these things. People had mixed reactions when I asked them. Most of my close friends understood me and chalked it up to me being inquisitive and weird. Some of my friends thought it was funny that I was doing this, and others thought it was creepy. (Little did they know that within a few years this would be commonplace-- there would be companies creating robots to monitor almost every action they took in life. At the time, behavioral targeting (or the ads you see targeted towards you when you’re online were terrible—guys with lives that revolved around playing fantasy sports would be shown ads for getting maternal eggs harvested. Ads are now a lot more accurate because they use these types of data to understand people) From this work, we ultimately published a pretty interesting paper on how to read behind the lines of what it really means when people change their relationship status. This was one of the first papers I know using social data to predict things.
At the same time, I was studying how to use technologies to prevent the spread of HIV. We were building online communities based on behavior change science, through an approach we called Harnessing Online Peer Education (HOPE). HOPE had people at risk for HIV join our online communities. (Since those initial studies we found that the HOPE approach has been pretty successful. In multiple studies in different groups across the world, we’ve seen HOPE get people engaged in long-term behavior change that sticks.) But we found something interesting happening. People were invited to private HOPE online community groups but immediately were sharing really personal information to strangers in the group, like what is was like being a married man who has sex with other men without telling his wife, or types of illegal drugs people were using. If people were instantly sharing such personal information with strangers through our HOPE communities, then perhaps they were also doing it on sites that were more public, like Twitter. The advantage to searching here was that Twitter provides access to a ton of their data, so we would be able to study “big data.” As I dug into the data, I was shocked at what people shared. There were a lot of people who had thought that social media was a pointless fad, a way for people and businesses to self-promote, and that it had no potential for social good. As I looked through the data, I thought I was finding a gold mine for advancing research in a ton of areas. Not to mention I was really excited because I wouldn’t be able to do 1/10th of the work on my own. I’d need to rejoin with my engineering friends I missed from graduate school and get their help. And I’d be able to learn a lot along the way about how people in different fields do research.
2. I can see from your research work on HIV that Twitter has played a critical role in your ability to predict the spread of disease. Can this be applied to influenza and less extreme cases, or is there something specific about HIV on social media that made those results possible?
Twitter and other social media can definitely be applied to influenza and other areas. In fact, it’s easier to apply it to those areas. As long as people feel comfortable and free using social technologies, then theoretically we should be able to use data from these technologies to predict almost anything. The limiting factor is whether we have what is called “gold standard data,” or data on actual events occurring (like cases where people have contracted HIV or influenza), as well as the frequency of getting those data. For example, influenza data are provided frequently, every week I think. That makes it much easier to create models to predict influenza compared to something like HIV, where national data on HIV cases are released about 2 years after they occur. That means that there’s huge value if we can predict HIV. It’s 2015 right now and we won’t know until well into 2016 or 2017 how many HIV cases occurred. If we can use social data to predict that number a little earlier it could have a huge impact on people’s health, it could reduce disease, save money, and prolong people’s lives.
3. Is there some fundamental truth about social media that lends itself to public health? For example, 30 years ago, if I dedicated myself to hooking up with an anonymous stranger for unprotected sex, I might scribble my phone number on a bathroom stall at a rest stop gas station. If Sean Young, PhD existed as an HIV prevention advocate in the early 1980's, would you be calling up gas station owners for frequent reports on the latest bathroom stall graffiti?
That’s an interesting question. I wouldn’t say there is a fundamental truth about social media or social data. As a psychologist, I would say that everything that people do leaves a trace of their psychology. The trick is knowing how to interpret what they do and read between the lines to know what it means. Not everyone would write on a bathroom wall, and of the people that would, they would only do it in certain times and contexts. (I’ll save people from my bathroom humor by not describing when some of those times would be). Social media is no different. There isn’t anything unique about us being able to get data on people’s behaviors from social media that we couldn’t get from other places. The point is that there is sooooo much data—for example 500 million tweets a day --- that it’s easy to analyze the data. Researchers want as much data as possible to confirm their hypotheses. Because there’s so much social data it gives us the ability to test and refine hypotheses about why people do things and how we can use this information to predict and solve real-world problems.
4. If you could have a face to face with the CTO of Twitter and request some changes to their technology that would improve health outcomes and prevent disasters, what would they be?
Ha ha. You’re touching on some things I used to think about from a social entrepreneurial perspective back in the day, like building a Twitter designed to get people working together to solve important global issues. Twitter’s most recent earnings call shows they’re having some major business problems with an uncertain future so I’d let Jack off the hook and let him figure out what to do with Twitter first. After that, I’d ask him whether he’d be willing to help with an effort to bring together companies with large amounts of data like Facebook, Twitter, Snapchat, and Google, to have them provide access to public health researchers. Then he’d probably laugh and never talk to me again.
5. What clues do human beings leave on social media that they are about to hurt themselves or others? Are there some big flashing signs that society is missing and should be educated about?
There’s no quick answer for this. Psychologists know you have to observe people over time to understand their patterns. Clinicians can look for certain signs like people not making consistent eye contact to know something might be wrong. There are ways of translating this to social media. But the clearest example would be the college student in October 2014 who talked on Twitter about his fear and disgust about his own and other people’s lives. A month later he killed 3 students and then took his own life.
6. Looking at what's trending on social media now, including my own, is there a glaring prediction for some coming cataclysmic event that you can share with me?
A big drop in the stock market.
7. Has there ever been a moment, working with predictive technology, that you have felt compelled to have someone committed to psychiatric care or call the police to warn of a crime?
No. So far we’ve been working at a population level, or looking at large groups of people to learn about their patterns. More recently, we’re studying individuals and so it’s likely I’d get those moments in the future. There’s still an interesting ethical question about whether and when people should act on those insights and actually intervene.
8. You work in the Family Medicine Department at the David Geffen School of Medicine at UCLA. How can physicians and therapists use social media to gain greater insight into their patients? Do you foresee Twitter feeds becoming a diagnostic data type formally integrated into electronic health records?
While these questions are focused primarily on Twitter, there’s a lot more than Twitter that can be used to provide predictive information to help in areas like public health and medicine. Other forms of social media, like Instagram, as well as wearable device data and search data all provides insights about behavior too. The department and the health system as a whole is already interested in applying some of our research. For example, the health system has asked me to be involved in integrating social data with medical records data to learn how we can have a more complete picture of patient health. Also, we’ve built a technology platform used to change patient behavior that is being tested on UCLA patients to improve their health. We’ll be able to use the data from studies and technologies like that to better understand patient needs, increase patient engagement/retention, and improve delivery of care.
9. From a theoretical perspective, is there anything in the work of Sigmund Freud, Alfred Adler or the other pioneers of psychology that prepared you for your research? Is there anything that you find yourself returning to philosophically?
I remember an early psychology course I took in grad school at Stanford. The professor began the class by saying, this is a psychology class and so many of you might think of Freud. Almost everything that we’ll study has already been mentioned in some way by Freud. But there’s no basis for most of ideas. He wasn’t a scientist. That’s why there are barely any psychologists who still practice Freudian psychoanalysis or teach his theories. We use science to study our ideas and so this will be the last mention you’ll hear of Freud in this class.
As a social and behavioral psychologist, most of my theories come from classic psychologists like Kurt Lewin, Leon Festinger, Stanley Milgram, and Daniel Kahneman/Amos Tversky; my graduate school mentors like Lee Ross, Benoit Monin, Albert Bandura, Claude Steele, and Bob Zajonc; and friends and colleagues like Danny Oppenheimer, Dave Nussbaum, Jonah Berger, Chris Bryan, and Hal Hirschfield.
10. Are you planning future studies that incorporate Snapchat, Instagram, Whatsapp or other social media technologies?
We’re in conversations like that right now and so I’m not sure what the companies would allow me to divulge at this point, but the short answer is yes.