Suzy Moat




Suzy Moat is an Assistant Professor of Behavioural Science at Warwick Business School. Her work exploits data from sources such as Google, Wikipedia and Flickr, to investigate whether data from the Internet can help us measure and even predict human behaviour.

In recent studies, in collaboration with Tobias Preis, H. Eugene Stanley and colleagues, Moat has provided evidence that patterns in searches for financial information on Wikipedia and Google may have offered clues to subsequent stock market moves, and that Internet users from countries with a higher per capita GDP are more likely to search for information about years in the future than years in the past.

Moat was awarded a Ph.D. from the University of Edinburgh and won a series of prizes during her studies. Since 2011, Moat has secured £3.3 million of funding from UK, EU and US research agencies. Her work has been featured by television, radio and press worldwide, including recent pieces on CNN and the BBC.

Moat has acted as an advisor to government and public bodies on the predictive capabilities of big data. She currently co-directs a data science research team working on these questions.

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May 22nd 2017

Join us to explore how the vast amounts of data generated today can help us understand and even predict how humans behave. We increasingly rely on networked computer systems and smart cards to support our everyday activities, and everything we do generates data – whether buying bread at the supermarket, taking a ride on public transport, or calling a friend for a chat.

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