James Fowler on the Power of Social Networks

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James H. Fowler earned a PhD from Harvard in 2003 and is currently Professor of Medical Genetics and Political Science at the University of California, San Diego. His work lies at the intersection of the natural and social sciences, with a focus on social networks, behavior, evolution, politics, genetics, and big data.

James was was named one of Foreign Policy’s Top 100 Global Thinkers, TechCrunch’s Top 20 Most Innovative People in Democracy, and Most Original Thinker of the year by The McLaughlin Group. Together with Nicholas Christakis, James wrote a book on social networks for a general audience called Connected. Connected has been translated into twenty languages, named an Editor’s Choice by the New York Times Book Review, and featured in Wired, Oprah’s Reading Guide, Business Week’s Best Books of the Year, and a cover story in New York Times Magazine.

And we are very happy to host him September 2 in skatepark Waalhalla for Social Science for Startups. This is your last chance to buy tickets.

Your book Connected has introduced me to the science behind our social networks. It is a mind opening book. I even made my wife read it (and she loved it). After that, people like Duncan Watts and Sinan Aral also did a great job in pushing the science of social networks further and at the same time popularizing it.

For those who are not familiar with your work, what are the main insights you gained on networks, and why should businesses bother themselves with these insights?

Friendship networks are powerful in (at least) four ways that may be useful for businesses:

1. Friends as data. We tend to have friends who do what we do, feel what we feel, and think what we think. So if I don’t know anything about you but I know something about your friend, then I can use that information to make predictions about you. And since we have many friends online, all of these pieces of information add up, giving us a better picture of a potential customer or client.

2. Friends as motivators. Friends often exert a powerful influence on one another. So if you want to reach a person, it might actually be more effective to reach out to their friends. In our study of drinking behavior, men were more susceptible to heavy drinking, but women were more influential, so paradoxically, efforts to reduce drinking might work better by targeting the women rather than the men. If you don’t map the networks of your customers or clients, you won’t know who to target.

3. Friends as multipliers. Social networks are exponential. If the average person has 5 close friends, then they have 25 friends of friends and 125 friends of friends of friends. So a single change in one person can spread and influence many more. This what we found in our 61 million person Facebook experiment where we got 60,000 people to vote with a single message on the newsfeed. Remarkably, the friends of people who saw the message were also more likely to vote, increasing turnout by another 280,000 people. So for every one person reached directly, another 4-5 people where reached indirectly, multiplying the effect of the message. This means if you aren’t measuring the effect of your efforts on the friends of your clients or customers, you may be missing the whole story!

4. Friends as sensors. Our work on H1N1 flu showed that people at the center of the network tend to get the flu first — if you have a dozen friends, you are likely to get infected sooner than if you only have one or two. In fact, our sample of “central” individuals got the flu about two weeks before everyone else. And our new work shows the same principle applies to Twitter, where we can predict what will go viral weeks in advance simply by monitoring central actors in the network. In other words, you the social network is a crystal ball!

You have been working with the Data Science team of Facebook, which we know intimately ourselves (Dean Eckles and our Co-founder Maurits Kaptein often work together on persuasion profiling and new research). This is one startup that turned into a great research opportunity for you I guess. And there are more companies that gather mindboggling amounts of data. It is for too simple to say that businesses now know more about their customers than they know themselves.

But do you know of any examples where social network data gave businesses insights about their customers that they otherwise would never have found?

Yes, a company called Activate Networks (for which I am a scientific advisor) has been working with a number of clients to map networks and use them to identify influential people in order to improve behavior change targeting. For example, they have worked with pharmaceutical companies to get doctors to switch to generic drugs and with health insurers to get employees and members of the community involved in exercise programs. These efforts have typically doubled the effectiveness of outreach efforts. They have also mapped employee networks to identify key information bottlenecks during mergers. These networks can be rewired to increase information flow and productivity.

So startups, and the internet as a whole has given scientists more opportunity to run new kind of experiments, gaining more insight in human behavior.

If I would give you 5 million dollars you could invest in a startup, what new technology would you want to be developed? And why?

I would want a social network that helps anyone to organize their own community. We have great networks for information sharing (Twitter), socializing with friends (Facebook), and networking with colleagues (LinkedIn), but these are all open networks, and as a result people may not feel as safe sharing information about their passions or connecting to other people who have the same goals. The open internet is a critical part of our life online, but we also need walled gardens where we can spend time with people who care about exactly what we care about.

This is why I’m working with a start-up called Backplane. They have built a community platform for artists like Lady Gaga, for social leaders like Nelson Mandela, and world-renowned brands like Coca Cola. And we are working to identify the online tools that help community organizers recruit new members and connect them to one another in order to create amazing content and organize real world activities. My hope is that this is the kind of platform that could help all communities around the world to thrive.

You say that you focus on social networks, behavior, evolution, politics, genetics, and big data. I personally love that. Normally this would mean someone has completely no focus whatsoever. But in your case I guess it is the essence of your work. Our company “only” focuses on behavior and big data, but we see that the science of social networks more and more ties into behavioral sciences. For example how herding behavior affects how things spread through a social network.

Can you explain a bit more why you think it’s so important to combine different disciplines while researching human behavior?

I think it is important to combine disciplines because there are so many smart people working on so many problems that the chances are very good that some of the unsolved problems in one discipline have been solved in another. If you can just cut through all the jargon (sometimes you need a Rosetta Stone!) there is a lot of low hanging fruit.

The world needs both people who are deep and people who are broad. In academia I love being surrounded by so many people who are the world’s expert on a particular topic, but that’s not me (I have a short attention span!). Instead, what I try to do is to take insight from one world and bring it to another. I feel a bit like Marco Polo, bringing home treasures from afar. Early in my career it was challenging to be this kind of person because the system is designed to create experts who preside over their deep but narrow silos. But there are now so many opportunities for multidisciplinary work and my own institution (UCSD) is the perfect place for someone like me because it is young and energetic and open to ideas crossing frontiers.

And finally what 3 disciplines should a marketing scientist (or data driven marketeer) look out for in the future to get an “unfair” competitive advantage?

I think anyone interested in social media should learn about real world social networks (old school sociology). I’m constantly amazed at how many people misunderstand that we have the same brains and the same basic social patterns as we did 100,000 years ago. Technology changes some things like speed and scale, but the basic building blocks are still the same.

Anyone in big data should be keeping an eye on genomic biostatistics. There are billions of dollars being spent on developing new ways to find extremely weak signals in massive amounts of data, so it’s not surprising that many of the most recent advances in machine learning are coming from there.

And anyone interested in behavior should keep an eye on social physiology. Increasingly, body language from eye blinks to posture will be measured electronically and will signal a lot about a person’s basic characteristics and their current state of mind.

See you soon at Social Science for Startups!

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