Social Mood Conference  |  Socionomics Foundation

Big Data is changing the way social scientists understand human behavior. Dr. Suzy Moat’s pioneering work in this field seeks to understand what our everyday actions on the Internet can tell us about how we make decisions and plan for the future. The Warwick Business School professor’s cutting-edge research has garnered international acclaim, including features in New Scientist, The Guardian, CNN and the BBC.

SF: What do you plan to discuss at the Social Mood Conference?

Suzy Moat: The Internet has become a central part of our lives. Our everyday actions now generate volumes of data on what words we are searching for on Google, what pages we are looking at on Wikipedia and who we are talking to on Twitter. My work uses the vast amounts of data generated by our everyday use of technology to understand how humans behave, a goal strongly aligned with the efforts of social mood research. My talk will aim to illustrate how large-scale patterns of communication can help us understand large-scale patterns of behavior.

SF: How is the emergence of Big Data changing what we know about how people behave?

Suzy Moat: Previously, our only ways of measuring how humans behave was to put them in an experiment, or ask them to write down answers for a survey. Now, we increasingly rely on networked computer systems and smart cards to support our everyday activities. Everything we do generates data, whether we’re buying bread at the supermarket, taking a ride on the subway or calling a friend for a chat. My colleagues and I argue that this data is opening up a new era for the science of human behavior.
SF: What are some insights into social behavior that you have uncovered in your work?
Suzy Moat: My work is currently focused on investigating data from Internet sources such as Google, Wikipedia and Flickr to determine whether it can help us measure and even predict real world human behavior. My recent work with Tobias Preis, H. Eugene Stanley and colleagues has led to some extremely intriguing results. For example, our research showed that Internet users from countries with a higher per capita GDP are more likely to search for information about the future. We have also found evidence that patterns in searches for financial information on Wikipedia and Google may have offered clues to subsequent stock market moves.
SF: How did your research background prepare you to become a computational social scientist?
Suzy Moat: I’ve always been fascinated by how humans behave and communicate, and my background is deeply interdisciplinary. My undergraduate and graduate training was in computer science, psychology and linguistics, and I’ve spent time in physics, math, sociology and civil engineering departments along the way. This has left me with a toolbox of quantitative and computational skills to dig into these fascinating new datasets which capture human behavior at such an immense scale.
SF: How would you like to see your research make a difference in the world?
Suzy Moat: As individuals, companies and governments, we decide how to act based on our best estimates of what’s happening in the world right now, and what might happen in the world in the future. I hope our work will help support better decision making by creating quicker and cheaper methods for measuring the state of our society today and improving our abilities to foresee problems which may occur in the future.
SF: Are there skills that young people need to acquire in order to contribute to Big Data research?
Suzy Moat: Learning to program is crucial. Thanks to my parents, I’ve been programming since I was 7. The UK government has now realized that they need to teach all children this essential skill. This is a vital move, as the value of this data for business, government and individuals who want to make better-informed decisions is immense. We need to train people with the right spectrum of skills to extract it.
SF: Why are you looking forward to talking about your research at the Social Mood Conference?
Suzy Moat: I hugely enjoy being able to bring different areas of research together. It’s fantastic to have an opportunity to talk to such an interdisciplinary audience about this work, and I’m really looking forward to hearing their thoughts.
SF: Thank you, Professor Moat, and we look forward to welcoming you to Atlanta for the 4th Annual Social Mood Conference on April 5th.

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