Layer Cakes Can Prevent Cyberbullying

“R U gay, Robbie? I think you are!” “No one likes you,” “Stop skipping school pretending to be sick, just go kill yourself.”                   

Each week, Robert looks at his phone and finds 10 to 20 abusive text messages like these. He finds similar messages on Instagram and Snapchat calling him a loser. After months of keeping everything inside, one night he breaks down in tears in front of his mom at the dinner table. 

His mother, astonished, asks if he’s ok. Robert holds himself together enough to tell her he’s fine. He realizes that the only way to deal with the problem is to join in. He grabs his phone, pulls up an anonymous profile on Yik Yak, and pecks out a stream of insults to random users.

Cyberbullying has led to an increase in depression and suicide among young children. It’s a tremendous public health problem, but tweens and teens often don’t even realize they’re cyberbullying others. In addition, it’s a difficult problem to diagnose because children don’t like to talk about their online lives. So, how do we stop cyberbullying among youth?

In one study, researchers gave questionnaires to 2,186 middle and high school students. The aim of the study was to examine how frequently students were involved in cyberbullying and to understand the factors that contribute to bullying behavior. More specifically, the authors wanted to distinguish between three groups: victims, bullies, and bully–victims (i.e., students who reported both cyberbullying someone and being the victim of a bully).

Cyberbullying is a relatively new field of research, so it’s notable that this study included thousands of kids. What did the authors find?

First, a lot of students participate in cyberbullying! More than 30% of the participants identified as being a victim or a bully. More surprisingly, one in four students identified as being both a bully and victim during the previous three months.

When we look at these findings more closely, a few things are worth noting. First, in traditional bullying, bully–victims are usually the smallest group of concern, but in this study it was the most common group of students. Second, the authors found that girls were more often bully–victims. And finally, the three groups of children had some shared risk factors, including whether they shared passwords with their friends.

Other studies show that cyberbullying is practically an epidemic: 42% of teenagers with tech access reported being cyberbullied in the past year, and 81% of teens say bullying online is easier to get away with. As an adult, it can be easy to dismiss these statistics: spats usually erupt over trivial things like celebrities or gossip, and fights are sometimes forgotten the day after they begin. But it’s important to remember that cyberbullying often leads to face-to-face confrontations and some students become afraid to go to school.

So, what do these findings mean for parents and teachers? As soon as kids start controlling digital devices on their own, talk with them about the potential risks and rewards of online communication. As they grow older and more proficient with technology, you can add other elements to your talks. I refer to this as the “Layer Cake Method” of online education. For example, you can start with a base-layer talk about netiquette and then move on to topics like online predators, identity theft, and Internet porn. During these talks, it’s important to emphasize that anonymity makes it easier to be a bully, and that respect in online communication is just as important as it is in real life. Finally, being more open about the dangers of cyberbullying may help reduce the risk of young girls reciprocating with bullying behavior.  

Cyberbullying poses a serious challenge, but there are many resources available if you feel overwhelmed. Most importantly, there’s a clear protocol to follow when cyberbullying happens. Research shows that victims rarely share their experiences, so it’s up to authority figures to be aware of the fact that schools, technology providers, and local governments have policies in place that can help resolve problems before they get out of hand.

The (Social Media) Doctor Is In: Twitter Can Be Used to Monitor Health

“I hate Donald Trump!” “I’m exhausted and my boss doesn’t care,” “I'm jealous of my sister's new car.”

If this is what your tweets look like, then you might want to reconsider your words: research shows you may be at risk for heart disease. Most people don’t realize it, but the language they use in social media posts can be used to predict their well-being, like their risk for heart disease or other serious conditions. How can social media be used to monitor people’s health and overall well-being?

In one study, researchers evaluated 100 million tweets from 1,300 counties in the United States. The language in these tweets was analyzed and categorized as having either negative or positive sentiment. Then, the authors separated the words of each tweet into word clouds that reflected “risky” language (e.g., despise, hate, jealous, tired) or “protective” language (e.g., opportunity, strength, hope, great).

Using machine learning methods, the authors created algorithms that compared the sentiment of the tweets from each county to CDC data on causes of death. Their findings were dramatic: counties whose tweets expressed more negative emotion (e.g., tweets filled with words such as “hate”) had more heart disease–related deaths compared to counties that featured tweets with more protective language.

When looking further into the data, the methods worked very well at predicting death from hardening of the arteries (atherosclerosis), which is the leading cause of death in the United States. It’s interesting that the people who were tweeting were not the people whose deaths were measured. Instead, the overall tone of the tweets — which were from people too young to be suffering from heart problems — appeared “to have captured a snapshot of the psychology of the community at large.” The authors had therefore discovered a similar result to one that our own team found in an earlier study focusing on HIV.

The authors claim that their methods predicted death from heart disease more accurately than risk factors such as obesity, smoking, and diabetes. Moreover, the prediction accuracy remained strong even after they considered classic predictors of heart disease such as education as poverty. These claims might make you raise your eyebrows, but decades of research has shown that the words people use shows a lot about their psychology. In this case, the algorithms created by the researchers were able to predict personality traits. In fact, the authors claim the algorithms they developed predicted personality traits as well as or better than friends who filled out personality surveys about the participants!

So, how does this research impact your life? For one, an entirely new field of research, known as “digital epidemiology,” has sprung up around social media. Now that social media is widely used (65% of American adults visit social media sites regularly, and 90% of young adults use at least one service), doctors and researchers have an entirely new tool to predict communitywide well-being. Healthcare providers already monitor Google searches to forecast disease outbreaks (e.g., flu, malaria, STDs), which helps determine where resources should be allocated.

For individuals, the hope is that as more and more people use social media, health predictions will become even better. For example, future studies may ask patients to provide access to their social media accounts when they go to an emergency room or visit their primary care doctor. Language in postings and status updates could provide clues to the risk for depression, which is a major risk factor in the recurrence of many diseases. And existing studies have already helped identify post-partum depression among new mothers.

If trends are any indication, social media is going to become even more popular and integrated into tools to solve real-world problems. I’m hopeful that we’ll find ways to use social media to predict other leading causes of death in the near future, and that we’ll find an effective way to protect personal privacy at the same time.

FAQ with Sean Young, PhD

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.