Suzy Moat is Professor of Behavioural Science at Warwick Business School, where she co-directs the Data Science Lab. She is also a Turing Fellow of The Alan Turing Institute. Her research investigates whether data on our usage of the Internet, from sources such as Google, Twitter, Wikipedia and Flickr can help us measure and predict human behaviour in the real world. The results of her work have been featured by television, radio and press worldwide, by outlets such as CNN, BBC, The Guardian, Wall Street Journal, New Scientist and Wired, and published in journals such as Proceedings of the National Academy of Sciences. She has acted as an advisor to government and public bodies on related topics. Moat studied Computer Science at UCL and Psychology at Edinburgh, during which time she won prizes including the UCL Faculty of Engineering Medal.
Everyday usage of the Internet leaves huge volumes of text and images in its wake. Suzy's research draws on these new data sources, and asks: can we use online data to measure human behaviour and experience we couldn’t measure before? Can we generate quicker, cheaper indicators of the wellbeing of society? Can we use these new data sources to predict human behaviour? Her previous work has touched on problems as diverse as linking online behaviour to stock market moves (with Preis, Curme, Stanley, et al.), estimating crowd sizes (with Botta and Preis) and evaluating whether the beauty of the environment we live in might affect our health (with Seresinhe and Preis). She is interested in generating indicators to support decision making in a range of domains, including economics and health.